# Aerodynamic Benefits by Optimizing Cycling Posture
## 3 Results for Determining Aerodynamic Drag
### Main Findings from Flow Simulation  
The flow velocity of 10 m/s was used to fit for typical Reynolds numbers. Values for the cyclist and the bike are presented in Figure 6. The impacts of the four different cycling positions are very clear. While the initial HH position shows CdA values in the range of 0.42 and 0.47, and therefore, the worst values, the TT position shows the best performance with CdA values between 0.22 and 0.24 Moreover, the two more comfortable positions (HH and HD) seem to be significantly more vulnerable to crosswinds, especially at 5-10\({}^{\circ}\) wind yaw: see the CdA that is higher by 0.034 (HH) or 0.033 (HD). The more aggressive positions (DB and TT) show more stability in crosswinds. They even tend to decrease at higher wind yaw. The TT position is even more favorable to crosswind then the DB position, with a CdA that is lower by 0.022-0.150. The yaw-dependence of CdA-values, shown Figure 6 reveals that all positions except (TT) show some increase at non-zero values, but only TT's CdA seems to decrease with higher yaw angles. This is somewhat counter-intuitive, as the projected area at least increases by simply looking at the geometry.  
Figure 5: Machine learning algorithm _ExPose_ shows the conversion from a 2D image to a 3D file.  
The corresponding flow wake along the models, sliced for the flow velocity in y-direction, is presented in Figure 7, showing large areas of _dead air_. Those areas of low speed often combine with regions of under-pressure, causing large areas of pressure-drag. Compared to the flow wake of the HH position at 20\({}^{\circ}\), however, the flow wake in the TT position is a lot smoother and less disturbed.  
Figure 7 gives an impression of the near-wake structure. Black areas indicate negative velocities, zones of re-circulating flow. It is well known that avoidance of these regions gives rise to reduced drag.  
Figure 6: CdA values for the cyclist and the bike at 10 m/s as a function of yaw.  
Figure 7: Flow wake for the HH position at 20\({}^{\circ}\) yaw; model sliced along y- axis.  
Additionally, to the CdA values, the resulting power output at 10 m/s was calculated. (In the example, the temperature T was set to 15.3 \({}^{\circ}\)C and aerodynamical drag was split into parts of 70% (cyclist) and 30% (bike).) While the HH position requires 190 \(\pm\) 10 W for the cyclist or 270 \(\pm\) 15 W including the bike for a speed of 10 m/s, the TT position only requires 50% of that power for the same speed, so 97 \(\pm\) 8 W for the cyclist and 140 \(\pm\) 12 W for the entire system. In the HD position, savings of around 8% compared to the HH positions can be observed. For the DB position, even higher savings of around 37% can be found, which makes the DB position the second fastest after the TT position. The calculated power output indicates very well the impact of cycling posture and the considerable energy savings that can be achieved.  
These investigations make clear that the favorable TT position requires only half of the power compared to the HH position. Results from flow simulation may be summarized as follows:  
* The lowest CdA value of 0.150 was reached for the TT position at 20\({}^{\circ}\).
* The highest CdA value of 0.328 was reached for the HH position at 5\({}^{\circ}\).
* Overall, the TT position showed the best performance.
* The TT position requires only half of the power output for the same speed as the HH position.
* DB and TT positions show much more stable performance in crosswinds, decreasing the crosswind's effect at higher wind yaw.