In brief, the theory of operation is that there’s a force sensor at each part where the rider meets the bike: handlebars, saddle, and pedals. Because Newton’s Third Law of Motion requires that aerodynamic forces on the rider must be fully transfered to the bike – or else the rider is separating from the bike – the forces on these sensors will total to the overall aerodynamic forces acting on the rider.
From a theoretical perspective, this is actually sound, and would detect aero forces from any direction, regardless of if it’s caused by clothes (eg a hoodie flailing in the air) or a cross-wind. It does require an assumption that the rider not contact any other parts of the bike, which is reasonable for racing bikes.
But the practical issue is that while aero forces are totalized with this method, it provides zero insight into where the forces are being generated from. This makes it hard to determine what rider position will optimize airflow for a given condition. To make aero improvements like this becomes a game of guess-and-check. Whereas in a wind tunnel, identifying zones of turbulent air is fairly easy, using – among other things – smoke to see how the air travels around the rider. The magnitude of the turbulent regions can then be quantified individually, which helps paint a picture of where improvements can be made.
For that reason alone, this is not at all a “wind tunnel killer”. It can certainly still find use, since it yields in-field measurements that can complement laboratory data. Though I’m skeptical about how a rider would even respond if given real-time info about their body’s current aerodynamic drag. Should they start tacking side to side? Tuck further in?
More data can be useful, but one of the unfortunate trends from the Big Data explosion is the assumption that more data is always useful. If that were true, everyone would always be advised to undergo every preventative medical diagnostics annually, irrespective of risk. Whereas the current reality is that overdiagnosis is a real problem now precisely because some doctors and patients are caught in that false assumption.
My conclusion: technically feasible but seems gimmicky.
But the practical issue is that while aero forces are totalized with this method, it provides zero insight into where the forces are being generated from.
This is true, and you’d need to do more tests to get to the same conclusion as when you used a wind tunnel.
However, this may still offer a significant advatage for teams, pro athletes, and even manufacturers of bike stuff.
For example, with all things being equal, you can very easily see if a certail wheel is creating more resistance over another. Same with certain clothing, or position on the bike.
It can still offer insights without needing to resort to a very expensive wind tunnel test (often out of budget for even researchers).
This is a very accessible piece of tech that will no doubt offer more studies to be fast tracked without needing to raise massive funds.
For example, with all things being equal, you can very easily see if a certain wheel is creating more resistance over another.
But this product cannot compute drag figures for the bike. Its theory of operation limits it to compute only the drag upon the rider. Also, to keep things simple in my original answer, I didn’t touch upon the complex bike+rider aerodynamic interactions, such as when turbulent air off the bike is actually alleviated by the presence of the rider, but thus moves a net-smaller drag from the bike onto the rider. Optimizing for lowest rider drag could end up increasing the bike’s drag, inadvertently increasing overall drag.
But I think the real issue is the “all else being equal” part. If a team is trying to test optimal rider positions, then the only sensible way to test that in-field is to do A/B testing and hope for similar conditions. If the conditions aren’t similar enough, the only option is more runs. All to answer something which putting the rider+bike into a wind tunnel would have quickly answered. Guess-and-check is not a time-efficient solution for finding improvements.
Do I think all bike racing teams need a 24/7 wind tunnel? No, definitely not. For reference, the Wright Brothers built their own small wind tunnel to do small-scale testing, so it’s not like racing teams are out of options between this product and a full-blown (pun intended) wind tunnel. And of course, in the 21st Century, we have a rich library of shared aerodynamic research on racing bikes to lean on, plus fluid modeling software.
If a team is trying to test optimal rider positions, then the only sensible way to test that in-field is to do A/B testing and hope for similar conditions.
But that’s the catch. You can never get similar conditions in the field, so this device can give you numbers in real-time.
For a rider in a race, this can help them optimize their position as wind speed and direction, as well as drag or terrain changes.
I can personally see many advantages to having this gear available
All to answer something which putting the rider+bike into a wind tunnel would have quickly answered.
Quickly, yes. But under controlled conditions, removed from external variables that could have an even greater relevance to the rider.
And all for much too much money for most.
Guess-and-check is not a time-efficient solution for finding improvements.
This provides data much like a power meter or heart rate monitor.
Once riders and teams begin to add this extra metric to their training or real-time races, I think they’ll have an advantage over riders and teams who don’t.
This was my assumption as well. If this is allowed on bikes during races, it is a really valuable tool to allow riders to tune their position continuously for the most efficiency.
My initial reaction was “this cannot work”. So I looked at their website, which is mostly puffery and other flowery language. But to their credit, they’ve got two
studies, err papers, err preprints, uhPDFs, one of which describes their validation of their product against wind tunnel results.In brief, the theory of operation is that there’s a force sensor at each part where the rider meets the bike: handlebars, saddle, and pedals. Because Newton’s Third Law of Motion requires that aerodynamic forces on the rider must be fully transfered to the bike – or else the rider is separating from the bike – the forces on these sensors will total to the overall aerodynamic forces acting on the rider.
From a theoretical perspective, this is actually sound, and would detect aero forces from any direction, regardless of if it’s caused by clothes (eg a hoodie flailing in the air) or a cross-wind. It does require an assumption that the rider not contact any other parts of the bike, which is reasonable for racing bikes.
But the practical issue is that while aero forces are totalized with this method, it provides zero insight into where the forces are being generated from. This makes it hard to determine what rider position will optimize airflow for a given condition. To make aero improvements like this becomes a game of guess-and-check. Whereas in a wind tunnel, identifying zones of turbulent air is fairly easy, using – among other things – smoke to see how the air travels around the rider. The magnitude of the turbulent regions can then be quantified individually, which helps paint a picture of where improvements can be made.
For that reason alone, this is not at all a “wind tunnel killer”. It can certainly still find use, since it yields in-field measurements that can complement laboratory data. Though I’m skeptical about how a rider would even respond if given real-time info about their body’s current aerodynamic drag. Should they start tacking side to side? Tuck further in?
More data can be useful, but one of the unfortunate trends from the Big Data explosion is the assumption that more data is always useful. If that were true, everyone would always be advised to undergo every preventative medical diagnostics annually, irrespective of risk. Whereas the current reality is that overdiagnosis is a real problem now precisely because some doctors and patients are caught in that false assumption.
My conclusion: technically feasible but seems gimmicky.
This is true, and you’d need to do more tests to get to the same conclusion as when you used a wind tunnel.
However, this may still offer a significant advatage for teams, pro athletes, and even manufacturers of bike stuff.
For example, with all things being equal, you can very easily see if a certail wheel is creating more resistance over another. Same with certain clothing, or position on the bike.
It can still offer insights without needing to resort to a very expensive wind tunnel test (often out of budget for even researchers).
This is a very accessible piece of tech that will no doubt offer more studies to be fast tracked without needing to raise massive funds.
But this product cannot compute drag figures for the bike. Its theory of operation limits it to compute only the drag upon the rider. Also, to keep things simple in my original answer, I didn’t touch upon the complex bike+rider aerodynamic interactions, such as when turbulent air off the bike is actually alleviated by the presence of the rider, but thus moves a net-smaller drag from the bike onto the rider. Optimizing for lowest rider drag could end up increasing the bike’s drag, inadvertently increasing overall drag.
But I think the real issue is the “all else being equal” part. If a team is trying to test optimal rider positions, then the only sensible way to test that in-field is to do A/B testing and hope for similar conditions. If the conditions aren’t similar enough, the only option is more runs. All to answer something which putting the rider+bike into a wind tunnel would have quickly answered. Guess-and-check is not a time-efficient solution for finding improvements.
Do I think all bike racing teams need a 24/7 wind tunnel? No, definitely not. For reference, the Wright Brothers built their own small wind tunnel to do small-scale testing, so it’s not like racing teams are out of options between this product and a full-blown (pun intended) wind tunnel. And of course, in the 21st Century, we have a rich library of shared aerodynamic research on racing bikes to lean on, plus fluid modeling software.
But that’s the catch. You can never get similar conditions in the field, so this device can give you numbers in real-time.
For a rider in a race, this can help them optimize their position as wind speed and direction, as well as drag or terrain changes.
I can personally see many advantages to having this gear available
Quickly, yes. But under controlled conditions, removed from external variables that could have an even greater relevance to the rider.
And all for much too much money for most.
This provides data much like a power meter or heart rate monitor.
Once riders and teams begin to add this extra metric to their training or real-time races, I think they’ll have an advantage over riders and teams who don’t.
This was my assumption as well. If this is allowed on bikes during races, it is a really valuable tool to allow riders to tune their position continuously for the most efficiency.