Some kilometres are longer than others

With the spate of attempts at the UCI world hour record over late-2014 and into 2015 due to the revised UCI rules making the record within reach of more riders, it has naturally sparked interest in discussing what matters for best performance in the event.

Jens Voigt started the latest round of hour record attempts at the UCI's Aigle track

I recently saw some chat on a triathlon forum speculating about who could do what distance and so on. All in good fun, but none of them actually go to a track to find out. If they did, they'd realise it's not quite as simple (or as hard) as they might make out.

It pretty much comes down to optimising four main elements:

• maximising sustainable power output for an hour
• minimising the physical resistance factors of riding on the track
• technical execution / skill
• logistics & resources

Some might add psychological factors to that list, but ultimately I consider these to be expressed within the outcomes of each of the above.

Regarding logistics, there are of course UCI requirements to be permitted an official attempt an hour record, e.g.: minimum time in anti-doping bio-passport program is mandatory at elite level or dope testing at age group level, application submitted in advance for approval to relevant levels of cycling administrations, all the technical requirements including international level commissaires to supervise, a UCI approved track, use of timing equipment, start gates, specified date and time of attempt, etc. You can't just rock up and ride whenever you like. Well you could but it would never be a sanctioned attempt.

Then of course you need to factor in enough solo rider time on track for preparation, and that costs money and time as well. Quality indoor tracks are not always local, and even if they are, getting solo time on the track is not always so easy, let alone cheap. For an elite professional rider whose job is to race on the road, it may be difficult to devote sufficient time to the task of preparing properly for a track event.

Of course assuming the paperwork is all in order and you can do your training, then sustainable aerobic power and aerodynamics are king and the rider's ratio of power to aerodynamic drag area is the single most important factor for how far they will go in the hour. But W/m^2 is not the only factor.

There are other physical resistance force factors, like the influence of air density which is a function of altitude, temperature and barometric pressure (and to a much lesser extent, humidity) and the rolling resistance of the track and tyres chosen. I discuss some of these in the following items:
Altitude and the Hour record Part I
Altitude and the Hour record Part II

Which leaves us with technical execution and skill factors, of which there are a couple of key items, namely:

• pacing, which I covered in this case study of the masters hour record by Jayson Austin, and 
• riding a good lines around the track.

Riding good lines

Riding a good line involves a couple of components, one is pretty obvious and involves not riding further than you need to around the bends. Ride wide and you ride further. Pretty simple given the track is all but two semi-circles joined together with two straight sections. OK, the actual shape of tracks are more subtlety curved but that's close enough to describe why riding wide adds distance to your travels around a lap.

Design of the Glasgow Velodrome

If you ride 10cm wider in the turns, you add 10cm x 2 x PI = 62.8cm per lap.

If the extra width is measured on the track's surface, well the actual addition to the distance the wheel travels is reduced by the cosine of the banking angle. e.g. say the track's turns are, on average, banked at 40 degrees, and you ride 10cm above the black line. Then the actual additional track radius ridden is cosine (40 degrees) x 10cm = 7.7cm, and the additional distance per lap = 7.7cm x 2 x PI = 48.1cm. Nearly half a metre.

Do that over 200 laps or so for an elite hour record and you'll ride ~100 metres more than you need to. And that's for riding only a hand's width above the black line.

London Velodrome used for the 2012 Olympics

Another more subtle ride line factor involves the shape and design of the banking and in particular the transitions from the straights to the turns and back again, and whether it's advantageous to ride a slightly wider line in the straights to aid the transitions. On the straights you don't suffer the same severe distance penalty of riding a wider "radius" as you do when riding wide in the turns, so you can explore marginal gains in this manner.

However there is no simple or single answer to this, it depends on the rider and the track geometry - all of which have subtle differences. This is a somewhat more complex optimisation problem and I'm not going to delve into it here.

So putting aside these subtleties, the shortest distance around the turns is to ride the track's black measurement line* - ride any further out from the black line and you ride more distance each lap than is necessary. For the hour record you only get credit for the official lap distance each lap, which is typically 250 metres per lap on most modern standard indoor velodromes although some tracks are shorter and some are longer.

* it is possible to ride inside the black line, however in such timed track events like the hour there are foam blocks placed around the inside line of the track to ensure the riders don't. Very skilled riders can however ride fractionally under the black line on some tracks but it is risky as hitting the foam blocks can disrupt your effort and wash off some speed. The shape of the track in that small space between the black line and the wide blue section varies from track to track and it can be good or not so good to ride in.

Foam blocks discourage riders from riding inside the black measurement line.

Now why are some kilometres longer than others?

Office distance for the hour record =
(Official lap distance)  x  (Number of full laps completed within the hour)
+ a pro-rata distance calculated for the final incomplete lap

I won't go into the formula used by the UCI to calculate the pro-rata distance of the final lap (that's actually deserving of a blog post on its own as the regulations are remarkably confusing).

It matters not how far you actually ride, you'll only be credited with the official minimum lap distance per lap. This is why track riders and coaches are focussed on lap times and not with bike speed, since lap times are the integral of all performance elements. Power meter and other data loggers are of course valuable in parsing out the individual elements of performance that go into attaining lap times, and helping to prioritise development opportunities.

How good are riders at riding the minimum distance necessary?

It varies. Quite a lot. Skilled track riders are typically much better, which is what you'd expect. But what sort of penalty would an unskilled rider face if they started out on a track effort?

Of course we can do lots of maths to figure out how much extra distance on average a rider might cover if they ride wide by so much, but in reality riders move up and down the track, sometimes riding a good line, other times not so good. Some riders are just better at it than others and some adapt to the track more quickly than others.

It'd be so much better if we could simply measure what people actually do rather than speculate.

Which had me thinking. I have some data like that already...

Not so long ago I was doing some performance testing involving half a dozen pro-continental road racers at an indoor 250m velodrome. One of the features of the data logging system used for the tests is an ability to calculate the distance ridden per lap using the wheel's speed sensor data combined with track timing tapes to know precisely when they pass a specific points on the track. With some clever maths this is enough to nail the actual distance ridden each lap to high precision.

In amongst the test data were some solo efforts of at least 10% of the distance of an elite hour record attempt (i.e. 20+ laps of consistent effort) and several such runs by each of the six riders. I figured the runs needed to be long enough to reasonably approximate what a rider might be expected to do over a longer distance/duration.

Of course absolute accuracy of the distance the wheels travel depends on having an accurate wheel circumference value and that value not changing a lot while riding. So I'm not going to assume that the absolute accuracy was perfect, even though the absolute error might typically be somewhat less than 1%. More than that would require an error in tyre circumference assumption of 20mm, which is a lot for those used to measuring such things. However in our favour is that even if such an error existed, it would be a consistent bias error.

So rather than concern myself with absolute accuracy, I thought I'd compare the measured average lap distance for each run with the shortest recorded legitimate lap. In this way if there is any bias error, it's impact on this analysis is minimised (i.e. both measurements would be out by the same proportional amount). By legitimate lap, I mean a full lap not ridden below the black line.

Here's a table summarising data collected from the six riders (in no particular order). Each rider has multiple runs although I haven't identified the riders in the table. What the first column shows is the average lap distance per run less the minimum legitimate lap distance for that same run. The distances are of course distance travelled by the wheel.

Now the riders possibly could ride a tighter line than they actually did for their shortest legitimate lap, meaning that these distances likely underestimate the extra distance ridden when compared with riding very tight to the black line.

For the moment though let's assume the shortest lap they rode during each run was the best they are capable of doing. Since they actually did it, I think that's a reasonable assumption.

The average extra distance ridden per lap varies from one rider to another. One rider consistently rode only 0.3-0.4 metres more per lap than their shortest distance lap, while another was consistently riding more than 2 metres extra per lap on average compared with their shortest legitimate lap. The rider with smallest extra distance per lap had a track racing background.

The second column shows what that average extra lap distance would mean if extrapolated to riding 200 laps of a 250m track (an official distance of 50.000km). For one rider they would be riding nearly half a kilometre further than their track skilled team mate. Yet if both completed exactly 200 laps in the hour, each would be credited with riding precisely 50km, even though one rider's wheels had travelled nearly 500m further than the other's.

In this case, 50.5km = 50.0km. Some kilometres are longer than others.

So what's that extra 500m cost in power terms?

Well for a rider with a CdA of ~0.23m^2, that extra 500 metres travelled requires they output ~11-12 watts more than if they were able to ride a a better line.

Or they'd need to find a 3% reduction in CdA to make up for their skill deficiency.

Remember these were well skilled, well trained and experienced pro-continential road racers and finding an extra 10W or losing another 3% of aero drag coefficient isn't such an easy thing to do.

So no matter your current skill level and experience, if you're expecting to ride such an event yet you have never trained to become proficient riding on the track, well you might want to chop half a kilometre or so from your estimated distance covered based on your power and aero data alone.

Better still, just get to a track a find out what you can actually do.

Likewise, when estimating power, or W/m^2 from the official hour record distances, you might need to add some watts for the technical proficiency of the rider. The less proficient, the more power is required to attain the same official distance.

Read More......

The Sin of Crank Velocity

Crank and bike speed variations during a pedal stroke

This topic occasionally comes up in discussion in cycling forums – just how much does crank speed vary during a pedal stroke? And how much does this affect the accuracy of power meters?

If you are pedalling along at a steady rate and maintaining a consistent power output (in other words you are not attempting to accelerate or slow down) and are using circular chainrings, then the short answer is: not a lot.

But crank rotational velocity during a pedal stroke is not totally constant, there is some variation.

Of course anyone who has ridden a bike behind a derny or motor pace bike on flat terrain or at a velodrome knows they are able to ride consistently close to the rear guard or roller of the motorbike and not experience significant fore-aft movements during each pedal stroke.

Riders following a motor pacer manage to remain very close
to the pacer and don't experience large fore-aft relative motion.

Riders in a highly skilled team pursuit formation riding at high power outputs are also able to ride within centimetres of the wheel in front without experiencing major changes in velocity between riders during each pedal stroke, which if it did happen would of course be somewhat disastrous. Note the riders below are all at different phases in the pedal stroke:

Track Cycling World Championships 2014: GB women's team pursuit team
Image from: www.telegraph.co.uk

So even without any examination of the research, or doing any fancy modelling of the physics involved, we already know empirically there really isn't going to be large variations in bike and crank velocity.

So how much variation is there and what influences bike and crank speed during a pedal stroke?

When pedalling in a steady state manner, the main factors influencing the variability of crank velocity are:

• The average power being applied
• The manner and level of power variation during a pedal stroke
• The inertial load of the system (i.e. the speed and mass of the bike + rider, plus a little rotational inertia from rotating components)
• The resistance forces in play (i.e. air and rolling resistance, gravity, and changes in kinetic energy) and whether for example air resistance is dominant (e.g. when riding on flat terrain), or overcoming gravity is dominant (e.g. climbing a steep grade)
• The shape of the chainrings, or as in the case of some weirdo bike crank and pedal sets ups, the variable effective radius of the crank arms

Why do we care about crank velocity variation?

Apart from satisfying our curiosity on this somewhat esoteric matter, the answer does have a few practical applications with respect to cycling performance, one of which is to do with power meter accuracy. Others pertain to efforts seeking to eek out minor performance gains though examining mechanical adaptations to the bicycle drive train, such as design of non-circular chainrings. Whether these designs result in a performance improvement is debatable (the research is equivocal on the matter for sustainable aerobic power) and not the topic of this post, so I'll leave it there for now.

Power meter accuracy and crank rotational velocity

Many power meters, e.g. SRM, Quarq, Power2Max, Garmin Vector and Stages, rely on the assumption that crank speed during a pedal stroke does not vary (Powertap on the other hand assumes wheel speed does not vary during their fixed duration torque sampling period of 1 second).

This is an important assumption, since torque is sampled at a fixed frequency (e.g. at 200Hz for an SRM or somewhat lower, e.g. at 50-60Hz for other brands) and then those torque samples are averaged over a complete crank revolution. This averaging of torque over a full revolution to calculate power will only be accurate if the crank velocity does not vary much during the pedal stroke.

If however a rider pedals significantly more slowly during one part of a pedal stroke compared with another, then that slower part of the pedal stroke will be over-weighted in the average of total torque samples. Hence interest in examining the assumption about constant or near constant crank velocity during a pedal stroke.

So let’s look at some of the crank velocity variability factors I mentioned earlier.

Power application during a pedal stroke

It’s well known that when we pedal we apply torque to the cranks in a pulse-like manner, with each leg’s down-stroke moving from a phase of minimal propulsive power when the crank is vertical with the pedal at top dead centre, increasing propulsive force and power as the crank moves down towards the horizontal, and diminishing as the crank moves towards the vertical again with the pedal at bottom dead centre. It looks a little like this:

Image courtesy of:
http://www.rohloff.de/en/company/index.html

In steady state cycling we apply little if any propulsive force on the upstroke and some may in fact apply a little negative force (this is not necessarily a bad thing and is something often misunderstood about pedalling dynamics - but I digress).

This pulse-like power cycle is repeated by the opposite leg and crank arm, so that for each full revolution of the crank, we apply two pulses of power, mostly from the down-stroke push of each leg.

This pulsating nature of power application has been measured and is well reported in the scientific literature, and typically shows a wave-like sinusoidal pattern (i.e. it looks like a sine wave), which should come as no surprise given our legs act like two pistons pushing down on rotating crank arms.

Studies examining this go back many, many decades, e.g. this 1968 paper by Hoet at al as an example reported the following finding:

Those summary findings by Hoes et al have been consistently replicated in many subsequent studies.

Such analysis goes back even further, to the late 1800s. Pedal pressure was measured and shown in this book: Sharp, A. (1896). Bicycles and tricycles: an elementary treatise on their design and construction.

This fabulous old book (which covers a huge range of cycling physics and performance matters over 32 chapters and which Lee Childers at Alabama State University kindly referred me to) is available in scanned form online here:

https://archive.org/details/bicyclestricycl02shargoog

Here are image scans from four of the book's 561 pages showing pedal pressure measurements from various riding conditions on a fixed gear bicycle (flat track riding, ascending and even back pedalling when descending). Read from the bottom of page 268 - Section titled: 214 - Actual Pressure on Pedals.

The charts plot the measured pedal pressure, which is not the same as the tangential (propulsive) forces, a point made on page 270 - but even so we can see the basic shape of pedal forces follows this basic pattern. Indeed Sharp refers to such tangential pedal force measurement pedals designed by Mallard and Bardon, their "dynamometric pedals". I don't have a link to show these unfortunately. This was the late 1800s. What's old is new again.

Below is an image from the 1991 Coyle et al paper showing the measured crank torque applied by one leg through a full pedal stroke for each of the 15 riders in the study. We don’t need to inspect the plots too closely; the main point is we can readily see the approximately sinusoidal shape of torque applied to the cranks during the down-stroke phase, and the minimal torque applied during the upstroke phase.

The primary differences between riders are in the amplitude of the down-stroke phase of curve, and the shape of the upstroke phase, which mostly hovers around the zero line. As always, you can click on an image to see a larger version.

If you then imagine the opposite leg repeating the same type of torque application, then we can see we apply torque to the cranks in a pulsating wave-like, or sinusoidal, manner. This sinusoidal curve was also demonstrated in the 2007 Edwards et al paper which included the following plot of typical pedal torque applied by both legs for a full crank revolution:

So while not perfect sine wave-like application of torque, thinking of the force applied to the cranks as being sinusoidal-like is a very good first order approximation.

Users of indoor bike training systems like Computrainer, Wattbike or SRM's Torque Analysis System may have also seen similar torque output curves. Here’s a random example of an image of a Computrainer SpinScan plot I found with a quick Google search:

Now SpinScan is not as fine a resolution measurement tool as used in scientific study, but at least you can see that the same basic shape of the power output curve during a pedal stroke. Wattbike charts are typically displayed in polar chart format, so to avoid confusing things I won’t post a picture here but the same overall pattern of torque and power application is repeated, as they are with SRM's Torque Analysis system (although this is a very low power example from SRM's website):

One thing we can see with all these examples is how power doesn't generally drop all the way to zero while pedalling, and that it is often not symmetrical for left and right legs.

I have generated a sample sinusoidal power curve to reasonably approximate this pedal power pattern which I'll use for modelling I'll discuss later on. In this case it shows the power curve when pedalling with an average power of 250 watts at 90rpm (click on pic to see larger version):

Now this is by no means a perfect model of actual power application, and as can be seen from the various charts shown earlier, everyone pedals slightly differently, but it’s certainly a very good first order approximation to examine the issue of how much bike speed is affected by application of such a pulsating power curve. It matches the general shape of actual torque delivery delivery and the peak power is nearly double the average power, which also matches the torque profile measured experimentally many times, and at least since Hoet at al reported this in the 1960s.

Naturally the power curve is a function of both crank torque and crank velocity, but as we shall eventually see, the latter does not vary all that much, certainly not enough to make this first order approximation invalid for the purpose of answering this question.

So what effect does this pulsating variable power output have on bike and crank velocity?

Firstly I’ll look at an example of what’s actually been measured and reported in the scientific literature, and then I’ll examine the physics with some modelling.

Actual measurement of crank speed variations

Crank speed variations during a pedal stroke were reported in this paper by Tomoki Kitawaki & Hisao Oka: A measurement system for the bicycle crank angle using a wireless motion sensor attached to the crank arm, J Sci Cycling. Vol. 2(2), 13-19.

Here’s a link to a pdf of the paper I found in a Google search:
http://tinyurl.com/qapfoek

I'm referring to this paper in particular as it provides some helpful images and a full version is available online for anyone interested in examining it in more detail. Other studies have also measured crank velocity during pedalling and found similar results, but the data may not be available in the freely available public domain nor presented in such a convenient and helpful manner as needed for this discsussion.

Figure 6 of this study (shown below) summarises the measured variability in crank velocity over a range of power outputs for riders in three groups categorised as beginner, intermediate and expert level by their relative power to weight ratio being approximately 1.5W/kg, 2.25W/kg and 3W/kg respectively.

Crank velocity for each group is shown at two different cadences (70rpm and 100rpm) and was measured using two different crank velocity measurement systems (the study was primarily to examine the validity of a crank angle and velocity measurement system compared with a standard. As it turns out the two methods matched quite well). They also measured the crank velocity variations at the riders’ freely chosen cadence but did not provide charts for those data.

In this study, riders used their own bike on a CycleOps Powerbeam Pro trainer, which is a fairly typical and relatively low inertia indoor trainer.

It shows six charts. In each the crank rotational velocity relative to the average crank rotational velocity (i.e. the normalized crank rotational velocity) is plotted by crank angle for a complete pedal stroke. There are a series of dots and lines plotted in the charts, and these represent the normalized crank rotational velocity as measured using two different measurement systems.

The maximal variance in normalized crank rotational velocity occurs in the most powerful group of riders, and at the lowest pedal rate (70rpm). The variance in this case was around +/-3% and in all other cases the crank velocity variance was less than +/-2%.

Keep in mind this experiment was performed on a low inertia trainer. Why does this matter? 

It matters because a mechanical system (or an object) with lower inertial load will accelerate (or decelerate) more rapidly when a net force is applied to it compared with a system with greater initial inertial load. Many indoor trainers, like the Powerbeam Pro used in this study, have lower crank inertial loads for the same rear wheel speed compared with what a bike and rider riding out on the road typically possesses.

So what happens when we examine the case of a more realistic road-like inertial load scenario?

Since I’m unaware of published and validated crank velocity measurements readily available from actual on road riding (if anyone can point me to any please let me know), we can instead examine the physics of what happens to a bike’s speed when power is applied in this pulsing sinusoidal-like manner.

Forward integration - Balance sheet accounting for energy

To do that I use the technique of forward integration, a technique that’s really no more complicated than an accounting balance sheet but for energy rather than money.

On one side of the balance sheet is the energy supply coming via our legs, and the other side of the balance sheet is the energy demand, i.e. the power required to overcome various resistance forces such as air resistance, rolling resistance, gravity if changing height, and importantly resistance to changes in speed (kinetic energy). That energy balance sheet must remain in balance. It’s a fundamental law of nature.

At any point in time if we know a rider’s speed, their mass and that of their bike, the moment of inertia of their wheels, their coefficients of air and rolling resistance, the road gradient, and other small frictional loss factors, then we can calculate how much power is required for each of these various resistance forces, and when added together they tell us how much power is required to maintain that speed.

If a rider’s actual power output is different to that required to maintain the same speed, then the balance of power supply must result in a change in kinetic energy, and hence a change in speed.

If a rider is in deficit on the energy balance, then that deficit must come from somewhere and that means their kinetic energy (and hence speed) must reduce by the same amount accordingly. Put another way, they are not supplying sufficient power to maintain their original speed and must therefore slow down.

Conversely, if the rider is providing power in excess of that required to maintain their original speed then they will accelerate, and at a rate so that the increase in kinetic energy matches that energy surplus.

In the model these calculations are made for each brief moment in time, the net energy surplus or deficit for that initial speed is determined and converted to the exact change in speed required to maintain the energy balance.

Let’s examine what happens to a rider’s speed in a sample scenario.
250W, flat road @ 90rpm

Riding along at 90rpm on a dead flat road with no wind and with an average power of 250W at around 36km/h with:

• Bike + rider mass: 80kg (including wheel rim mass of 1kg)
• Coefficient of rolling resistance (Crr) of 0.005 (fairly typical for good road tyres on asphalt/chip seal surface)
• Coefficient of drag area (CdA) of 0.35m^2 (e.g. road bike on the hoods)
• Air density of 1.20kg/m^3 (sea level, 1020hPa, temp 21C, relative humidity 77%)
• Drivetrain efficiency:  100% (just to keep it simple, although ~97% is typical)

Using the forward integration model with the simulated sinusoidal-like power output during a pedal stroke, we can now plot the impact on bike speed during a pedal stroke. Click to view a larger image.

In the chart above we have the power output (yellow line) varying during the pedal stroke, which takes a total of 0.667 seconds to complete each revolution. The plot show 1 full second of pedalling, and so the graph actually shows one and half revolutions of the crank.

The initial velocity is set to a little under 36km/h. The speed resulting from that pulse like power input is also plotted by the blue line with the left hand axis being speed. Note the speed scale ranges from 24km/h to 40km/h and so is already zoomed in a little to amplify the variation. At that slightly zoomed scale we can see that the speed line wavers up and down just a little during the pedal stroke.

Since it’s a little hard to see how much variation in speed happens, let’s zoom in much more by adjusting the speed scale to amplify that speed variation curve.

Note the scale of the speed axis on the left side – each horizontal grid-line represents 0.05km/h, and the variation in speed is easier to see.

When power is higher than that required to maintain a constant speed, then speed increases. Eventually though the power drops below the level required to keep accelerating, and speed levels off then begins to decline as power has dropped such that there is now an energy deficit compared with that required to maintain that speed, and so kinetic energy (speed) must fall. As a result, the speed plot follows a similar sinusoidal-like curve, but out of phase with the power plot.

Here’s a table summarising the average, minimum, maximum and amount of variation in power and speed.

The normalized speed variation is less than +/-0.2%.

As I said, not a lot of variation in bike speeds during a pedal stroke, even though the power is ranging from a low of 20W up to a maximum of 480W twice each pedal stroke.

That's bike speed - what about crank velocity?

Now the next logical step is to assume that this “all-but” constant bike speed is also matched by constancy of chain speed and hence crank speed. Since the chain is moving around the rear wheel's circular cog and the upper drive section of the chain has positive tension then that is what you would expect.

So provided the front chainring is circular, this will also result in a nearly uniform crank rotational velocity.

Hence in this steady state cycling scenario we need not be concerned with any inaccuracies in power measurement due to the assumption used by power meters that crank velocity is constant during a pedal stroke.

For crank velocity not to closely match the bike’s velocity it would require the part of the chain under constant tension to stretch and contract significantly during each half pedal stroke, or for the chainring to not be circular. Chains just don’t do that but chainrings may be all sorts of curved shapes.

Sensitivities and assumptions

As I said earlier, this input power model is only a first order approximation; people apply power slightly differently, and not necessarily symmetrically or consistently. Some of the other assumptions may not necessarily hold, e.g. aerodynamic and rolling resistance coefficients, and drivetrain efficiency remaining constant during a pedal stroke when they may in fact vary a little during pedal stroke. The rider’s legs also slightly vary their kinetic and potential energy as they move through a pedal stroke,

These are second and third order effects that would only make minor changes to the shape of the modelled speed curve, and we can see that the speed variation is already so small such that second and third order modifications are not going to change the outcome to any significant degree.

What about when climbing a steep hill?

When climbing, average speed for same power will be significantly less than when on a flat road. On an 8% gradient our 250W rider will be travelling at closer to 13km/h instead of 36km/h. That’s means a much reduced kinetic energy – which is dominated by translational KE of the rider.

KE = 0.5*mass*velocity^2,  plus a little bit from wheel rotational inertia (which is very small).

The translational KE of our 80kg bike and rider at 36km/h is 4,000 joules, and at 13km/h it’s 522 joules, or only 13% of the KE at 36km/h, even though velocity is 36% of flat road speed.

The next big difference is the resistance forces are now dominated by overcoming gravity rather than overcoming air resistance. This also has an impact on the size of bike speed variations during a pedal stroke, the result being we should expect changes in speed to be greater.

Finally, many riders have a tendency to pedal at a lower cadence when climbing steep hills. Not everyone does of course, but sometimes the available gearing means a lower cadence is inevitable. So for the sake of this scenario, let’s assume the rider’s cadence has dropped to 60rpm (that's about what cadence would be with a 39x23 gear at 13km/h).

This is the power and speed plot:

Since the cadence is 60rpm, it take a full second for each pedal revolution. We can see even with the low zoom level on the speed axis that the bike’s speed line does indeed vary more than when on the flat road.

Here’s what the speed variation looks like using the same zoomed-in view setting as before:

So when climbing there is a much greater variation in bike speed during a pedal revolution than when riding on a flat road at higher speed, but it’s still less than +/-2%.

Is a +/-2% crank speed variance during a pedal stroke something to be concerned with for power meter accuracy? 

As a rough rule of thumb, the error this would introduce to the calculation of power would be approximately 40% of the crank speed variation, or less than 1%. Whether that 1% error matters to you I can't really say, but it's a couple of watts and for most people it's not a significant factor for the purposes they might be using power meter data from climbs for.

If you are doing some aerodynamic field testing though, then such an error would be of concern. Fortunately we don't do such testing on steep climbs all that much, but rather mostly on flatter terrain where any error due to crank rotational velocity variation as we have seen is tiny.

That’s a 3.5W/kg rider. What about a more powerful 5.5W/kg rider climbing that 8% grade?

More powerful riders climb faster, and likely pedal at a higher cadence as well, so let’s assume our 400W rider climbs the 8% grade and pedals at 75rpm (that's roughly the cadence if pedalling a 39x19 gear at 19 km/h). This is the resulting power and speed plots:

So even though the rider is more powerful and has much greater variation in power output, the increased cadence and higher speed means the normalized crank rotational velocity variation is only +/-1%, and power meter error is likely to be less than 0.4%.

Summary

While pedalling in a steady state manner out on the road with circular chainrings, crank speed does not vary all that much. It varies more when climbing than when riding along flatter terrain, but the amount of variation is still small such that the basic assumption of non-varying crank velocity used by power meters to calculate power is sufficiently valid and within their generally stated margins of error.

Crank speed variation is larger when riding on low inertia trainers, such that the level of potential error in reported power may begin to approach the limit of the devices' stated error margins.

Read More......

Resistance is futile, even for MTB

In February I posted an item, The sum of the parts, which discussed the energy demands of cycling, and explored the age old "wheel weight versus wheel aerodynamics" debate, and gave some examples of wheel choice by way of modelling the weight vs aero performance trade offs using a forward integration model to consider dynamic acceleration scenarios.

I'm going to return to dynamic modelling one day to explore more realistic acceleration power outputs than the constant power examples used, but not today. Modelling a dynamically changing scenario is a bit trickier than steady state (constant velocity) scenario, and it's the latter I'm posting about today, more for the record than anything else in particular. Hey, I was asked, so here goes.

Relative energy demand for steady state road cycling

In the introduction to that item was the chart below, which shows the relative energy demand for steady state cycling for each of the main resistance forces, for gradients ranging from flat (0%) to steep (10%). The idea being to show how the relative importantance of each resistance force varies with zero or positive gradients. The assumptions used are listed in the table on the chart. Click on the chart to see a larger version.

I didn't include negative gradients (descending), as the charting starts gets a little funky - since gravity in that scenario is aiding our forward motion, rather than resisting it. Suffice to say that air resistance is still dominant when going downhill. Besides we tend not to put out nearly as much power going downhills, and brakes also come into play depending on the terrain.

So back to non-negative gradient chit chat.

We can see how air resistance is the dominant resistance force on flatter terrain and hence why aerodynamics matters a lot on flatter and shallower gradients, gradually giving way to gravity which dominates as the climb becomes steeper and our speed slows. This is why weight is an important performance factor on the slopes but much less so on flat ground.

The assumptions used to generate the chart were for a road cyclist in a fairly aerodynamic road bike position, although one would expect them to ride in a less aerodynamic position as the slope steepens. These minor assumption variations don't really change the overall chart trend much.

How about for MTB?

If we change the input assumptions (e.g. CdA, rider mass) all that will happen is the overall trends will shift a bit to the left or right, so having those assumptions precisely right isn't really the point of the chart, it's more about how the components of proportional energy demand vary by gradient.

As an example of modifying those assumptions, a while back for Mountain Bike Magazine, to assist with an article discussing the relative merits of 26" and 19" wheels (see those wheel arguments happen everywhere!), I created the same chart shown below but used alternative input assumptions more akin to MTB riding.

We can see that the same pattern appears as for the road cyclist, however the relative importance of the various forces is somewhat different, and in particular note the larger relative energy demand of rolling resistance due to MTB tyres and rougher terrain. Still, aero still matters in MTB on the shallower terrain, and is something to consider with bike set up depending on the type of racing you do and course profile.

Of course cycle racing is not just about the physics of the energy demand factors or the physiology of energy supply (power output). Skill, experience, strategy, tactics, technical factors and psychology all play their part. This was simply to demonstrate the relative importance of the key physical factors involved.

Get more aero, get lighter, get quality tyres and get fitter. Simple really.

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An hour at a time - photos

Refer to yesterday's post for details on Jayson's record ride.

I'll post images, credits and links to images here.

Thanks to Donncha Redmond:
http://www.flickr.com/photos/47663040@N00/sets/72157632721745241/

Only one hour to go...

Getting lap splits, pacing instruction and time checks from coach

hold a good line Jayson...

387 turns...

last lap c'mon!!

A couple thanks to Nour "TrinewB" on Transitions:

can be lonely out there even though people are watching

on target...

These came from Jayson, from Ernie Smith I think...

track's that a way Jays!

tight suit

coach showing off his coach's physique

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An hour at a time

A short and sweet entry today. I'm just back from the Dunc Gray Velodrome, having coached rider Jayson Austin to a new world masters hour record for M40-44 category.

48.411km

which adds 1.284km to the previous record of 47.127km held by Dave Stevens (December 2011).

Great work Jayson, it was a bit of a fight with some challenges during the ride.

Coach is pretty darn pleased with his chargers - Jayson having previously set the record for M35-39 back in 2009 (you can read about that here) and just recently Charles McCulloch of the UK set the M50-54 record a few months back at the Manchester velodrome.

Charles' record for M50-54 is 47.96km. 

Across town and across the world. Good work fellas.

For those interested, here's Jayson's speed and cadence plot. I'm leaving the power data out for now, for reasons I won't go into here.

Photos later.

Post script: For reference, Jayson's ride is the second fastest hour ride ever by an Australian. Brad McGee holds that record at 50.052km, set in 1997 aged 21. Different and slightly more relaxed aero equipment rules back then.

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The sum of the parts

A perennial favourite argument on cycling forums is the cost-benefit of choosing a wheelset with superior aerodynamics vs a wheelset that is lighter (or an aero vs a lighter frame).

It is of course a false dichotomy that one must chose only one or the other. But that does not stop people having fun arguing the merits of each, or of holding onto beliefs/myths/folklore handed down through the generations. Of course there are a multitude of things that go into what is a suitable choice of wheels, and I'm not going to delve into those, suffice to say they involve a range of factors aside from aerodynamics and mass, including, inter alia (and not in any particular order):

• strength
• durability
• ability to stay round and true
• lateral stiffness
• cost
• repair-ability and service cost
• suitability for the purpose/race/riding situation
• braking demands
• handling characteristics
• available tyre choices
• bearing and freehub quality etc
• rules of competition
• suitability for the bike (e.g. will it fit?)
• sex appeal / bling factor
• and so on.....

Then one needs to weigh up those factors and apply their own personal judgement as to which factors matter most. That will of course be different for everyone. It's no wonder wheel manufacturers have a field day with all the various possible points of difference available when marketing their wares.

But let's get back to the issue of wheel mass and aerodynamics, and what actually matters if for instance we could assume that all other factors between two wheel sets were identical.

Just before diving into that - to slightly complicate matters, one might assume the rotational inertia of a wheel plays a big part in its performance during accelerations (over and above the simple difference in wheel mass itself). Well of course one should expect some difference between wheels with different moments of inertia, but is it really a factor of significance when it comes to acceleration performance?

Now this question has already been examined by others, including a good item on wheel performance by Kraig Willett at Bike Tech Review. In that item, Kraig runs through the physics and demonstrates how (in)significant a difference in wheel rotational inertia during accelerations is, relative to the other primary resistance forces encountered on a bike. In another, more simplified look, Tom Anhalt also examined this and illustrates the same finding in this article on Slowtwitch.

So one can reasonably ignore the difference in moments of inertia when considering overall acceleration performance. But for those who still care, the equations of motion for a cyclist have been developed, thoroughly tested and do include the moment of inertia. I'll get back this this soon.

So, back to weight v aero - the classic prize fight.

First let's consider the relative energy demands of the various resistance forces encountered when cycling, primarily:

1. air resistance (bike and rider's aerodynamics, speed and wind)
2. gravity (weight of bike and rider, and gradient)
3. rolling resistance (tyres and road surface)
4. drive-train friction losses
5. changes in kinetic energy (accelerations)

We can examine the difference in relative energy demand of the various resistance forces a rider encounters when riding at steady state speed on roads of various gradients. An example is shown in the chart below:

In this example, we can see the relative importance of each resistance force, as gradient changes from flat terrain (0% slope) to very steep (10% slope). As the road gets steeper, the influence of gravity takes over, and as the road flattens, then air resistance is the dominant force.

Our speed when climbing steeper gradients is directly and almost linearly proportional to our power to mass ratio. Hence why weight is a primary consideration when the road tilts upwards. Lose 2% mass for same power, as you'll go nearly 2% faster. Pretty simple.

However when the terrain is flatter, then it's not so simple as the relationship between speed and power is not pseudo-linear, but rather a cubic relationship with relative air speed, meaning that to sustain a speed that's 2% faster (1.02 times), you'll need nearly 8% 1.02^3 or approximately 6% more power*. Ouch. Talk about diminishing returns. That's why aerodynamics matters so much.

* when you really account for all the forces correctly, then the increase in power demand for an increase in sustained speed from say 40.0 to 40.8km/h (a 2% speed increase) is more like 5.5%, and you can use a exponent of 2.7 rather than 3 as a slightly better ROT.

But what about accelerations?

Well the power required to accelerate is directly proportional to the mass and the rate of acceleration. Of course there will also be a power demand to overcome the varying air and rolling resistances at those varying speeds, as well as deal with gravity for any hill we might be climbing at the time.

So it all starts to get a little more complicated. Bear with me...

Back in the 1990s, a group of bright sparks did a lot of testing to develop and validate a mathematical model for the physics of road cycling, and have that published in the peer reviewed scientific world. The model was developed after extensive testing at highly variable wind speeds and yaw angles, and has been tested against real world data collected using SRM power meters. It's since been adapted and validated for velodrome track scenarios including standing start accelerations by world class track sprinters. I don't have a website link for the paper, but here's the reference details. OK, I found the website link to the paper:

Validation of a Mathematical Model for Road Cycling Power

James C. Martin, Douglas C. Milliken, John E. Cobb, Kevin L. McFadden, Andrew R. Coggan. Journal of Applied Biomechanics, 1998, 14, 276-291

Some of you might recognise a few of the author's names. In summary, the equations look like this (as per a slide from one of Dr Coggan's powerpoint presentations):

At first glance it looks a bit OTT, but really it's not that bad once you break it down to its constituent parts.

What this fancy pants maths enables us to do is something called forward integration - which is a way of being able to predict the second by second speed of a rider if we know their second by second power, and a handful of key variables like their aerodynamic drag coefficient, weight, tyre rolling resistance, gradient, wind and so on.

Now there are some websites that have been doing this stuff for years, and the best example I can think of is Tom Compton's analyticcycling.com. Check it out, Tom does some cool modelling.

For a bit of fun though, I thought I'd examine two acceleration scenarios using the forward integration technique to examine the performance trade off between a wheel set that's more aerodynamic versus one that's a bit lighter.

Here are the two scenarios.

Scenario 1:
A rider accelerates from a standing start with an average power of 1000 watts for 10 seconds.

Scenario 2:
A rider accelerates from 30km/h with an average power of 1000 watts for 10 seconds.

I'm going to use the following as assumptions on the differences in key variables:

Bike set up A: CdA of 0.320m^2 and mass of 80.0kg (lighter but less aero)

Bike set up B: CdA of 0.297m^2 and mass of 80.5kg (heavier but better aero)

and the following assumptions apply to both bike set ups:

Air density: 1.2kg/m^3

Crr: 0.005

Drivetrain efficiency: 100%

No wind

I chose that difference in CdA as it is representative of a real world difference I have measured between two rear wheels (one a low profile light-ish 32 spoke wheel, the other a wheel designed solely for aerodynamic performance), although for the purpose of this exercise, I have exaggerated the mass difference.

By using the equations of motion, and the technique of forward integration, in this case using a time interval of 0.1 seconds, we can show what happens when we accelerate from a standing start. Here is the speed plot for those 10 seconds for each bike set up:

Well, the lines pretty much overlap, but as you get closer to the end of the acceleration  we can see that the heavier, but more aero set up results in a higher top speed after 10 seconds. But does that mean they are ahead? If they were initially slower in the early phases of the acceleration, will they catch up? Well to examine that, we simply inspect the difference in cumulative distance travelled at each time point:

So, now we can see that initially after starting together, the rider with the heavier but more aero wheel falls behind slightly in the opening seconds and the distance grows initially until they lose a maximum of 4.6cm on their "rival" after 4.3 seconds. But after that point, the rider on the heavier and more aero wheel begins to catch up, eventually overtake his rival after 7 seconds, and wins the 10-second sprint by 17cm, or about 1/4 of a wheel. For even just a half lap track sprint, that's way more than enough to justify the aero option over the weight penalty. But if your speciality events lasts less than 6 seconds from a standing start, then go for the lighter rim.

OK, but what about accelerating from a rolling start?

Well let's examine the same scenario, with the only change being that we start at 30km/h, then apply an average of 1000W for 10 seconds. Speed difference plot:

Again we can see that the speed lines are closely matched, except now the top speed reached after 10 seconds is higher and the top speed difference of 0.5km/h between each set up is larger than the top speed difference in the standing start scenario. And the gap in distance? 

Well this time the lighter/less aero wheel loses out straight away and never gains an advantage. The guy with the heavier but more aero wheel wins the 10-second sprint by 60cm - nearly a full wheel width.

OK, so if flattish terrain is your thing, and regular accelerations are part of the game, then perhaps a re-think about the relative merits of aerodynamics and weight when considering which wheels to use. And keep in mind that for the purpose of this exercise I over exaggerated the typical mass difference, while using a fairly typical improvement in aerodynamics attainable from using a deep section aero wheel set over a lighter low profile wheel.

For my next trick, I will examine the shape of a typical power curve during such accelerations, and apply that variable power supply to the models, since nobody really accelerates with a flat power curve. Look out for Part II.

And as they say in the trade, YMMV.

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Another Hour of Power

48.317 km.

That’s how far Jayson Austin was calculated to have ridden on his second and successful attempt to set a new world record for Masters Men (35-39) distance ridden in one hour. It added a huge 2.676km (5.8%) to the previous record set in 2007 by Jason Sprouse of the USA.

Jayson on his way to a new World Record

It is also the second furthest ridden by an Australian, with Brad McGee holding the honour of the furthest distance (not sure exactly how far but it is something over 50km).


It’s also about the same length as this post, so be warned!

I wrote about Jayson’s previous unsuccessful attempt in this post: An Hour of Power, which has been one of the more popular reads on this blog.

So what went right this time? How did Jayson add a whopping 3.649km (8.2%) to his previous attempt where he managed to ride 44.668km?

More excellent photos on the ride taken by Trevor Mullins can be found here:
http://tregan.com.au/photography/Sport/Cycling/One_Hour_Record/

As I have mentioned before, there are three things that primarily contribute to a fast time trial (or in the case of the hour record, to maximise distance ridden):

• Power to the pedals
• Piercing the wind (plus fast tyres)
• Pacing the course

I’ve previously explained these Three Ps in this post: Old Skool.

OK, well let’s consider his first attempt at the record last year.

Power - Feb 2008
Average Power: 241 watts (4.0 W/kg)
Normalised Power: 259 watts (NP:AP = 1.07)

Jayson took quite ill in the weeks leading up to the event and he was clearly not in the form he would have normally expected come race day. In hindsight he probably should have postponed. However that is a difficult choice as the logistics to organise the event make that tricky. In addition, on the day the timing system failed and Jayson had to abandon the attempt after 5-minutes and do a restart. That certainly did not help his cause at all. Jayson also chose to use a gear far too large for his form on the day.

Average Power for his first attempt was 241 watts. Normalised Power was 259 watts, giving a ratio of NP to AP of 1.07. For an hour record attempt, that is a very high ratio and one would expect a very well paced effort on a velodrome would see that ratio being very close to 1.00.

Piercing the wind - Feb 2008
Using the data available from the SRM power meter on Jayson’s bike, I concluded his CdA (a measure of how slippery you are through the air) was in the vicinity of 0.190m^2. That is very slippery for a bike rider by any standard. So Jayson had a pretty slick set up and position. Riding 44.7km with an average power of only 241 watts certainly indicates he was piercing the wind just fine.

Combined with his power, the ratio that most determines the speed a time trial rider will travel at is their sustainable power to aerodynamic drag - FTP : CdA - ratio.

In Feb 2007 that ratio was 241 / 0.190 = 1268 W/m^2

Pacing - Feb 2008
In essence, in the context of his sub-standard form come race day, Jayson simply paced poorly, making the classic mistake of going out too hard and fading. Badly. Ignoring the pacing signals from his coach, this was well and truly demonstrated by the charts in the first linked post, showing how much he faded through the course of the attempt, finally hitting a brick wall at around the 45-min mark.

Breaking his average power down into 15-min sections shows the dramatic fade in power:
00-15 min: 302 watts
15-30 min: 272 watts
30-45 min: 242 watts
45-60 min: 151 watts

I suspect what Jayson did was to ride at a level he felt he would be able sustain but that turned out not to be the case. C'est la vie.

Using my pacing analysis models (something I haven’t written about in any detail here), I have rated Jayson’s pacing with a Pacing Score of 0.960, which is, in fact, the lower anchor point on my relative pacing performance charts (i.e. indicating very poor pacing). A best in class Pacing Score is 0.995 (with 1.000 being theoretically perfect pacing).

To put that into context, if Jayson had ridden with best in class pacing, even with the reduced power at his disposal on that day, he could have added another 1.5-1.6km to his ride distance. He missed the record that day by 974 metres.

These are tough mistakes to make and hard lessons learned. But we often learn more from having the courage to make mistakes. Certainly both Jayson and his coach would have felt a little burned by the attempt (what some may not know is that Jayson had, in training, already beaten the record, just not officially sanctioned with UCI supervision, electronic timing, doping control etc etc that is required for an official record to be set).

In the months following, Jayson’s riding, form and morale slipped somewhat and his coach (a friend of mine), who was moving onto other projects, suggested Jayson speak with me about taking him on and getting him back on track. So Jayson and I discussed where he was at and set ourselves the objective of having another crack at the hour (as well as other racing objectives along the way).

For me, what was going to be important was that Jayson demonstrated a willingness to learn from the mistakes made (both from the ride specifically but also in general). You can be sure that these lessons were not lost on coach, and I consider them to be a substantial contributor to Jayson’s excellent performance the other week.

The biggest failure this time round would not have been missing the record, but in repeating the same mistakes.

OK, so how did the successful ride compare?

Power - Apr 2009
Average Power: 302 watts (5.0 W/kg).
Normalised Power: 303 watts (NP:AP = 1.00)

That’s 61 watts (+25%) more than his previous attempt. Now that’s gotta help. How did he manage it?

This time round Jayson did not get ill before the event. Nevertheless he is still relatively prone to illness, niggles and for some reason, a little accident prone as well (he even had a crash a few weeks before the attempt which did disrupt preparations a little). Jayson also works a full time job, with a lot of manual labour required (he works in the commercial flooring industry). So the ramp up of his training loads were pretty carefully managed to avoid increased susceptibility to illness and at times recognise that his work was sometimes tough on his body and training needed to be cut back. Even so, there were times when Jayson would do more than coach liked, and guess what? – the niggles would appear soon afterwards and training would be compromised.

Over time Jayson really started to appreciate the sense behind carefully managing the training loads. It enabled consistency of training and from that follows a steady and sustainable improvement in form. Jayson told me his form “sort of snuck up on me”.

Of course I did not confine Jayson to just training. Racing was a reasonably regular part of the diet. Every rider needs that little extra motivation at times, and pinning a number on your back is an excellent way to do this. As well, in the final weeks before the attempt, we minimised his exposure to Sydney’s busy roads, with a majority of rides being either with me, a trusted mate, at Centennial Park, on the velodrome or on my purpose built ergobike, Thunderbird 7.

Clearly Jayson has an engine and can really dig out some excellent power at times. What he lacked when we began working together, some 40 weeks before his hour ride, was depth of fitness. Despite very low training loads, he is way too capable of putting the hurt on and suffering the consequences. For those that understand the numbers, his chronic training load (CTL) at the time we started was ~38 TSS/day.

At the time of his hour ride:
CTL: 86 TSS/day
TSB: +10 TSS/day (training stress balance)
CTL/ATL Time Constants: 42/7 days

I did not have Jayson doing huge volumes. What I did do was ensure Jayson was doing quality work. Good solid endurance. Plenty of sweet spot / tempo work. Threshold tolerance work. And during the specific race preparation period, high end aerobic power work and specific threshold work on the track bike and in aero position at the track. The limited taper involved cutting back volume while using short but relatively intense intervals at the higher end of his aerobic power level abilities.

Here is a comparison of his power last time and this time:



Piercing the wind - Apr 2009
OK, so I have already established that Jayson was pretty darn slick through the air. But was any further improvement possible? Well yes as a matter of fact. Some positional changes, a different set of aero bars (based on a British Cycling design) and use of double disk wheels resulted in Jayson’s CdA lowering to around 0.185m^2. That’s a 2.6% improvement. It doesn’t sound a lot but that is worth approximately another 420 metres to his ride.

The bike exactly as ridden.
Thoroughly checked to ensure full compliance with all UCI regulations.
Note placement of the SRM PCV under the saddle.

Of note was that on this attempt, Jayson rode with a standard "under ball of foot" cleat position. In Feb 2008, Jayson used a mid-foot/arch cleat position. The fact that improved aerodynamics was achieveable despite the higher saddle position required of the regular cleat position would not be lost on some astute readers. Jayson also received a lot of support from fit guru Steve Hogg, mainly addressing many of the regular niggles, minor adjustments, use of various stem options, different saddles etc.

During training at the track, where possible, changes in position or equipment were compared to assess the differences. An alternative aero helmet was tried for instance and found to be substantially less aerodynamic than the Uvex that Jayson used. This is one of the direct and practical benefits of using power meters. It removes much of the guess work and objective decisions can be made based on the data.

So now Jason's FTP:CdA ratio is 302 / 0.185 = 1632 W/m^2

Even so, I would say that further improvement with his aerodynamics is still possible. There are still several minor details which, with enough solo track time, I would like to have tried and tested but they will just have to wait for another day.

Pacing - Apr 2009
Well I’m glad to report that Jayson now has the unique honour of topping the pacing league table, with a Pacing Score of 0.998, the best score I have ever recorded, as well as being the low anchor point (0.960).

Let’s just say that of the things that were drummed into Jayson’s head, pacing was what I was most concerned with. I knew he had the power. I knew he was slick. But would he be able to execute?

To ensure that happened, we did a lot of work in the weeks leading up to the attempt focussed on pacing. I developed a means to clearly communicate pacing information to him and Jayson began to develop an excellent “feel” for how to augment his effort ever so slightly each lap to maintain a sustainable pacing level. His choice of gearing was part of that strategy.

One thing went against the “conventional wisdom” – Jayson’s average cadence was 112 rpm. Conventional wisdom says Hour Records are all but set with a cadence of ~100rpm give or take 1 or 2 rpm. Bollocks to conventional wisdom I say.

Pacing information, lap times etc were conveyed on a regular basis

We also knew that different environmental conditions would impact on the sustainable pace on the day and we trained on different days with subtly different conditions. On the day of the attempt I checked both the air temperature and air pressure and that would tell me what pacing would likely be sustainable (and what wouldn’t). Dunc Gray Velodrome is not climate controlled and the temperature can and does vary quite a lot.

For example, a 5C drop in temperature would reduce the distance ridden by ~ 280 metres and an increase in air pressure of 20hPa would mean another 315 metres lost. Fortunately it was not a cold (21C) nor a high pressure (1004hPa) day although it had been warmer in training. Also, we requested that all windows and louvres be closed so as to minimise any potential wind disrutption and to retain as much heat inside as possible (April is Autumn in Sydney).

Of course the athlete is the one that must make a call on how hard to go but I had developed a very good understanding of his body language and could tell when it was too hard. Jayson was never going to go too easy, that’s for sure. My main concern was keeping a lid on it in the opening minutes. Jayson was made well aware of the lap times and how that played out relative to the existing record. The pacing mistakes were made in training, and ironed out in training.

On race day, nerves and adrenaline took a hold (I expected it, heck coach was nervous too!) and Jayson’s pacing was a little up and down in the opening minutes. However he made rapid adjustments knowing full well what over cooking it would do. It took quite a while but once he settled into a rhythm, his pacing was metronomic. Average lap times around the 250 metre track were 18.59 seconds (not counting the opening lap).

We had planned for a couple of “rest” breaks, where he could sit up, stretch, relieve any pressure points for a lap or so but as it turns out he didn’t need that and remained firmly in position for the entire hour. At times he varied his pace a little, and sometimes pushed himself back in the saddle, which was quite deliberate and helped him to stay comfortable and keep his concentration going.

Here is a comparison of his speed last time and this time:

That's more like it!

Thank you to:
Apart from Jays actually having the gumption to have another crack and delivering, there were many others involved in helping him get there and all should rightly share the success, including his former coach (hi Peter) who introduced him to training with power in the first place and showed what was possible, sponsors, the officials who helped coordinate the venue/UCI/ASADA etc, our club chief Mike, Jayson's family/support crew, Steve Hogg who was very accommodating with equipment and constant positional adjustments, training and racing buddies who kindly lent special gear (wheels, bars) for the attempt and rode/raced with Jays during the build up. And then all those that showed up to cheer him on!

Footnote:
Just six days after his record breaking ride, Jayson was knocked from his bike by a car while on a ride by a “hit and run” driver. Knocked unconscious and very, very nearly run over by another oncoming car, who’s driver managed to stop with the bumper bar over Jayson’s head, he is lucky to be alive. Jayson was admitted to Manly hospital and fortunately suffered no broken bones. However he did suffer from a sizeable haematoma and severe swelling of the thigh which required emergency surgery to open the leg (a fasciotomy) so that excess fluids could be drained and the swelling would not prevent blood flow. That was successful but now he has a large open wound which will take some weeks to heal.

He has since been discharged and it will be at least eight weeks before he can work or ride. As you can imagine Jayson is pretty pissed off about the incident but otherwise is in good spirits.

So now it will be onto the next challenge, getting an injured soul back to good form. That's something I have some experience with.

Well done Jayson! A super ride.

Photos: David Lane, Action Snaps:
http://www.actionsnaps.com.au/

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