“Making hard things easy” is a cornerstone of how we develop bramble. One such example of this is the automation of testing “car following car” models.  If you have ever tried this manually, you’ll know that duplicating and offsetting geometry and boundary conditions can be a time-consuming and error-prone process.  With bramble, simply specify the car’s offset (or offsets – we can run multiple cars following each other!) Then let bramble do the hard work.

Formula 1 race car

In order to demonstrate how we have implemented this, we thought it would be interesting to compare the overtaking aerodynamics of two generations of Ferrari F1 cars: the 1978 312T and the 2016 SF16.  In particular, we’ll look at how each cars aerodynamics is affected as they approach a lead car.

We’ve run both cars offset by 10m and 20m to see how aerodynamic performance changes as the following car approaches the lead.

Both vehicles have been set at ride heights of front 38mm, rear 93mm and run at 160kph.  Perhaps a sub-optimal ride height for the SF16, but we wanted to keep some similarity between the two tests.  All simulations are steady-state RANS using a k-omega SST turbulence model.

overtaking aerodynamics

Let’s start with some numbers…

The graphs below compare the relative downforce (left) and drag (right) levels of both cars with offset distance.  These forces are shown as a percentage of their respective “clean air” performance.

graph comparing downforce of SF16 and 312T with offset distance.
Converting RANS to DES - Solution Stage

The speed at which an F1 car can take a corner is, in part, governed by the amount of downforce it can produce.  The more downforce, the faster it can corner and then the better it can overtake.

From the data above, we can see that the 312T loses around 10% of its downforce at a 20m offset. This increases to 50% at 10m.

The impact on the SF16 is much more pronounced.  It loses 52% at 20m increasing to over 71% at 10m. The increased loss in performance of the SF16 compared to the 312T gives some credence to the view that overtaking has got harder in modern F1 cars.

It’s not all about downforce though.  In order to achieve high straight-line speeds, drag (or the lack thereof) is king.  Whilst the SF16 loses the most downforce, it also experiences a bigger reduction in drag. 40% at 10m compared to 10% for the 312T.  Relatively speaking, the SF16 will get a bigger “tow” from the lead-car making it easier to overtake in a straight-line.

So perhaps, overtaking hasn’t got harder in a modern F1 car, it is just harder to do in a corner.

Where is the downforce lost from?

bramble will automatically extract force distributions when a simulation completes.  These can be used to compare different models and, for example, can highlight where downforce is gained and lost.

The images below (click on them to enlarge) show the downforce distributions for the 312T (left) and the SF16 (right).  Each image contains the distribution for the “clean-air”, 10m-offset and 20m-offset.

showing the downforce distributions for the 312T
Converting RANS to DES - Solution Stage

Although the 312T loses some downforce from the front wing, particularly at the 10m offset (red line), the majority of the loss comes from the rear wing.

Whilst the SF16 also experiences a loss in downforce from the rear, it also suffers a much more significant loss on the front wing, even at the 20m offset.  This additional loss explains why the SF16’s performance is affected much more than the 312T’s.

To be continued…

In Part 2 of this blog, we’ll take a closer look at why the front wing on SF16 loses much more downforce than the 312T’s.

Thanks for reading and watch this space!

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