The results of Blocken's CFD study confirmed the 30 percent to 35 percent reduction in air resistance for the trailing rider, but they also showed there is an effect for the leading rider -- specifically, a reduction in resistance of about 2 percent to 2.5 percent, which even goes to 3 percent if there are additional trailing riders.
The physical explanation for the findings is that a cyclist experiences air resistance caused by the overpressure of the wind on the front part of his body, pushing him backwards, and by the underpressure on the back part of his body, which sucks him backward. This underpressure is determined by the "wake" or "slipstream" behind the back of the cyclist, so when a second cyclist rides behind the first, he or she fills the wake, reducing the underpressure, and, in turn, creating less air resistance for the first rider.
While 2.5 percent seems like a minor gain, Blocken says it can actually translate into quite an advantage in cutthroat competitions. According to his calculations, there can be a 50-second gain on a distance of 50 kilometers, which happens to be the time trial distance for the Tour de France.
"Because time trial races are often won with a time difference of a few seconds, the 2.5 percent can clearly be decisive and determine whether a team wins or loses a race," according to summary documents prepared by ANSYS on the study. "The same applies to sprint races, which are sometimes won based on a few centimeters that have to be decided by photo finish."
One other note about the study's findings: The 2.5 percent applies to cyclists with identical body shapes and sizes, so if the second cyclist is larger/wider/taller than the leading rider, the reduction in air resistance for the first one will be even greater, Blocken said. This can be particularly useful for competitive riding teams developing a riding strategy, according to Thierry Marchal, industry director at ANSYS.
"This could have a major impact on preparing a time trial for the Olympics to define a strategy of where to put people," Marchal explained. "If you look at six cyclists as a system, not everyone is equally strong. This helps you think about where to put people."
Well, this is great work. It is an interesting use of CAE to understand what is really happening in a sport. A lot of this type of study is done in swimming.
The only reservation I have is that it makes the whole thing more complicated. It will increase the cost of fielding a team since they will now have to purchase the CAE software and all the equipment for measuring athletes.
That is if the racing teams actually make an investment in this kind of research, but you're right. It does inject a level of complexity and cost into the equation. Then again, competitive sports teams make this kind of investment all the time. Professional football teams do all kinds of analysis and simulation, golf professionals do, and the list goes on.
Yes, it make it more complicated, but this type of complication is usually welcomed in competitive sports. Part of the competition is off-road, where teams study everything little item that can afford an advantage.
I was involved in the controls for a new soft drink bottling line last year. It was fascinating to watch 2-liter bottles move from the blow-molder to the filling machine on air-veyors. The bottle is supported by its neck, and the air-veyor blows air downstream, providing an almost frictionless conveying means. The bottles move very fast.
While the transport alone was neat to watch, the fascinating part was what happened to the bottles. Trailing bottles would catch up to the one in front of it, until about 6-8 bottles were moving along in a single slug. Physics and geometry created that optimum slug. No other bottles could catch up to it, so another slug would form behind it.
I would imagine there is an optimum cycle train as well, for a given average cyclist mass, speed, and cross-sectional area, not just the benefits of a pair of riders. That would seem to be the next path to explore.
Thanks for the question. We never counted the hours, but we have been working on the aerodynamics of single (isolated) cyclists since 2006. This studied was funded by the Flemish Cycling Union. It was a full-time job performed by postdoctoral fellow Erwin Koninckx for one year and a half. Also Thijs Defraeye (PhD student at the time) worked for almost 50% of the time during more than two years on this project. Both were supervised by Peter Hespel, Jan Carmeliet and me. Erwin was later hired by the Flemish Cycling Union and is working there now. Erwin was/is the perfect man for the job: he has a double master degree, one in engineering and one in biomedical kinesiology, as well as a PhD in biomedical kinesiology.
The second study, i.e. on the groups of cyclists, was started in 2009. I started this study as a personal initiative because I wanted to investigate what would happen with groups of cyclists. There was no funding for this initiative, but luckily I could count also on the enthusiasm and support from the previous collaborators: Erwin, Thijs, Peter Hespel and Jan Carmeliet. Also the wind tunnel team at Dutch-German Wind Tunnels was enthusiastic and gave us some free testing time. This study - with some interruptions due to other tasks - is still going further today. I think I have spent, overall, more than 6 months full time on this second study. But much of this was spread over the past three years, including many weekends and evenings. Although our computing cluster has been calculating almost continuously in the past 10 months, and is still doing so today.
Thank you for the comments and thanks Beth for the very nice article about our work. Here, I would like to acknowledge the other members of the team:
- Dr. Thijs Defraeye, Leuven University, Belgium - Dr. Erwin Koninckx, Flemish Cycling Union, Belgium - Prof.dr. Peter Hespel, Bakala Academy - Athletic Performance Center, Leuven University, Belgium - Prof.dr. Jan Carmeliet, ETH Zurich, Switzerland
Thanks for the update on the project and for sharing your work with us. Very, very interesting and sounds like there's more to be done. Can you give us an idea of what kind of computing cluster is churning through all these calculations over the last six months?
Hi Beth, the computations are performed by parallel processing on twelve HP DL360R07 Xeon X5650 2.66 GHz processors with 96 Gb RAM, although the full range of RAM memory has not been needed yet for this study - this will only be needed when we extend the group of cyclists to about 15-20.
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