Photo: AP

Bike races can be won by fractions of a second, so professional teams use every advantage to cut precious time. Improving aerodynamics is one of the legal advantages. Therefore, an understanding of aerodynamics can help to streamline bicycles, adjust rider positioning — and even change tactics.

Dr. Bert Blocken, researcher at Eindhoven University of Technology in the Netherlands, has dedicated himself to cycling aerodynamics. Using ANSYS Computational Fluid Dynamics (CFD) solutions, he visualizes air flow to get a better understanding of aerodynamics as it relates to road bike racing.

High air resistance regions indicated in red. Image from Sheffield Hallam University.

Ten years ago, researchers at Sheffield Hallam University noted high pressure areas — regions of high air resistance — on the human body when cycling. The head and neck-to-shoulder areas were high pressure, as expected, but so was the pelvic area.

CFD analysis led to a redesign of the bike frame. Image courtesy of Avanti.

Minimizing air resistance in bicycle structures has also been a design concern for a long time. For instance, moving the seat stay can result in a smoother flow of air over the wheel. Contouring the downtube into an arc just millimeters from the tire is common in carbon fiber time trial bikes.

But until recently little was studied about following and leading positions in a pace line – the close formation that riders will create. What effect do they have on the race? For that we must first look at fluid dynamic fundamentals.

Why is CFD Analysis Important? Because Intuition Can Fail!

Because air is invisible, how it behaves as it passes around objects is difficult to understand. Our intuition is based on what we observe or projections of observable behavior. This can lead to mistakes.

As an example, scientists were asked which arrangement in the figure below results in the highest wind speed through the gap. Almost all of them got it wrong.

What arrangement would produce the highest wind speed? Image courtesy of Eindhoven University of Technology

The answer is B. Intuition leads us to expect that flow through a converging shape will create a speedy jet of air, but as CFD results show below, the converging shapes (left) create a large upstream overpressure area (in blue) which acts like a dam, preventing wind from getting into the gap.

CFD analysis proves that the diverging arrangement increases air flow through the gap. Image courtesy of Eindhoven University of Technology

This phenomenon is known as upstream disturbance. It happens all the time with subsonic flow, and has significant applications to bike racing. The moral of the story? Perform CFD analysis and “don’t trust your intuition,” cautions Blocken.

CFD Answers: How Important is Upstream Disturbance?

Section of a 12 million cell hybrid mesh. Image courtesy of Image courtesy of Eindhoven University of Technology

“Using laser scanning technology, we can produce a mesh so fine you could see the wrinkles,” jokes Blocken. For his analysis, he used a 12-million-cell hybrid mesh of a cyclist and his surroundings that was tested using ANSYS CFD.

Using these scans, Blocken created controlled mesh designs to test the drag effect of a trailing cyclist on the leading cyclist. He then duplicated the test based on various seated positons of the two cyclists, including head and waist tilt angles, arm positioning, and other arrangements.

Drag reduction of the first cyclist based on second cyclist distance. Comparison of various rider seating positions. Image courtesy of Eindhoven University of Technology

A summary of the CFD analysis showed as much as a 2.7 percent drag reduction for the lead rider caused by the rear rider. That’s for both riders in a time trial position (orange) and with no distance between the wheels (d = 0 cm) – which is possible if the second rider is slightly off to one side.

A wind tunnel data point used to validate the simulations shows a little more than 1.5 percent reduction in drag. That was at 10 cm distance between the wheels and riders in the “drop” positon (blue). “These number are small but significant,” says Blocken.

Pressure map comparison of single and double riders. Image courtesy of Eindhoven University of Technology

A pressure map analysis shows that underpressure zones (blue line), which result in a backward force for the rider, get smaller for the lead cyclist when another rider is close behind.

In their words, the second cyclist “fills up” a void left by the first rider, which if left alone causes the backward force.

This effect was postulated in 1998 by other researchers, but their tests revealed no measureable effect and no CFD was done.

CFD Team Time Trial Analysis for the Tour de France

This year’s Tour de France features a team time trial. This race will include teams of several riders in a pace line. Given what we now know above, which cyclist in the team below do you think is working the least?

Image courtesy of Eindhoven University of Technology.

Many might be fooled to think the final rider will have the easiest ride. However, CFD shows that the second from the last rider is working the least. This is due to the widening wake with each rider in succession but the last rider gets no benefit from the effect of a rider behind him.

Upstream disturbance accounts for drag improvement for the second to last rider. Image courtesy of Eindhoven University of Technology

Does Upstream Disturbance Matter in a Race?

The big question is: will a 3 percent drag improvement change the outcome of the races?

“It will have little or no effect on races won by a sprint, as those can be quite chaotic and unpredictable,” says Blocken. “The same applies to long stage races, which can be won by a lone rider out in front in a break away.”

However, a team time trial is a different story. Here the riders create a close formation. As results from two different team time trials in 2013 show, the difference between first and second place can be as little as one-hundredth of a second.

CFD Discovers an Unfair Advantage

A car following closely will act to push the rider. Image courtesy of PezCyclingNews

After concluding that a trailing cyclist positively and significantly influences the leading cyclist, Blocken wondered about the effect of a car following a cyclist. Wouldn’t a bigger shape (the car) have more of an influence? What if a car followed one rider closely and not another? Could this affect the outcome?

Cars do follow cyclists in bike races, sometimes dangerously close. As you can see in the picture above, a car follows closely behind Fabian Cancellara at the conclusion of an individual time trial.

To answer these questions, a model of the car (a basic station wagon) and a cyclist was used to study the car effect with ANSYS CFD.

Pressure map indicates an unfair advantage is given to the rider due to the follow car. Image courtesy of Eindhoven University of Technology

Shown above is a car following 5 meters behind a cyclist. This is a violation of cycling rules, which forbid cars closer than 10 meters from a bike. But this rule is violated repeatedly and is rarely, if ever, enforced by race officials, says Blocken.

Looking at the pressure gradients from the simulation, you can see the large overpressure area (red) in front of the car. This overpressure reduces the underpressure area behind the cyclist, in effect pushing the rider forward. This is more of a factor on cold days, when the air is denser.

Time difference based on distance traveled and distance of the follow car. The follow car can give riders and advantage of over 100 seconds! Image courtesy of Eindhoven University of Technology

What would be the actual difference in seconds over a typical time trial?

According to Blocken’s analyses, even a car following a rider at the legal 10 meter distance produces an advantage to the rider. Over the course of a 50 km time trial, the car could decrease the finishing time by 3.9 seconds.

At an illegal — and dangerous — 3 meter distance, the car will affect the cyclist’s time by 62 seconds over a 50 km time trial. “In the Tour de France, this is the difference between being first and not even being in the top 10,” says Blocken.

Blocken concludes that a follow car distance of 30 meters should be mandated by the rules, since a car that far from the rider would truly have a negligible effect on the rider.

For more on ANSYS CFD and this research, watch Dr. Blocken’s webinar” "Will CFD Influence the Winner of the Tour de France?"

ANSYS has sponsored this post. They have no editorial input to this post — all opinions are mine. Roopinder Tara.