Formula One - Aerodynamics update 3 - within the margin of CFD error

#f1 #formula1 #aerodynamics Formula One - Aerodynamics update 3 - within the margin of CFD error For other aero updates: - Part 1: https://youtu.be/PgogIbld-Ko - Part 2: https://youtu.be/07ru0LfGl3c - Part 4: https://youtu.be/fPTmyrmEJn8 In this Aero update we wanted to reduce the flow separation at the top of the side pods. The air had way too much upward momentum to stay attached to the sharply angled top edge of the side pod. So based on community feedback and internal brainstorms, the Voyager - AirShaper team came up with the following design changes: 3a: Ferrari-inspired backward swept design The goal here is to have the top & bottom edge of the sidepods sweep backward to alleviate some of the pressure towards the outside. In the results we can see that flow separation at the top has been much reduced, but now there is some flow separation at the sides, as we're directing flow there. Good news though, that flow separation area looks to be smaller in size. 3b: Curved top geometry of the side pods The goal here is simple: provide a more gradual, upward curvature at the top edge of the side pod for the air to stay attached to. We can see in the results that flow separation has been reduced, but not eliminated. Also, as the air curves around this geometry it speeds up more than before, futher lowering the pressure. This creates a suction effect which can cancel out some of the downforce generated elsewhere on the car. 3c: wing profile to control the flow We added a wing profile just above the top edge of the side pod to force the airflow to take a sharper corner around the edge and to stay attached. In the CFD results, we can see that separation is slightly reduced at the outer parts of the sidepods, but not at the inner parts (where the local angle of attack is probably more aggressive). So the solution has potential, but would require a lot more tweaking to potentially make it work. Coefficient analysis All concepts score worse than Aero Update 2: they all have less downforce and all have more drag. So what is happening? Well, to get a very reliable averaged value, you need a lot of iterations. For normal design work, the length of the averaging window used at AirShaper (which keeps variations around max 1%) is enough. But for specific cases like this one, where we are looking at deltas of less than 1% in some cases, you would need to increase the length of the averaging window to get reliable drag coefficient and lift coefficient data. Still, we're able to obtain qualitative insights from these simulations, allowing us to make a pragmatic choice: we're going for the Ferrari design! Simulations: Original car: https://app.airshaper.com/projects/voyager-airshaper-adcc85 Aero Package 1: https://app.airshaper.com/projects/voyager-airshaper-20adc9 Aero Package 2: https://app.airshaper.com/projects/voyager-airshaper-4b4532 Aero Update 3a: https://app.airshaper.com/projects/aero-update-3-conc-afd350 Aero update 3b: https://app.airshaper.com/projects/aero-update-3-conc-845f3d Aero update 3c: https://app.airshaper.com/projects/aero-update-3-conc-18fb76 ---------------------------------------------------------------------------------------------------------- The AirShaper videos cover the basics of aerodynamics (aerodynamic drag, drag & lift coefficients, boundary layer theory, flow separation, reynolds number...), simulation aspects (computational fluid dynamics, CFD meshing, ...) and aerodynamic testing (wind tunnel testing, flow visualization, ...). We then use those basics to explain the aerodynamics of (race) cars (aerodynamic efficiency of electric vehicles, aerodynamic drag, downforce, aero maps, formula one aerodynamics, ...), drones and airplanes (propellers, airfoils, electric aviation, eVTOLS, ...), motorcycles (wind buffeting, motogp aerodynamics, ...) and more! For more information, visit www.airshaper.com