It has long been debated, and to an extent accepted, that the regulations have stifled creativity of design in Formula One, but is it now possible that this has spread to creativity in simulation methodology? The long and the short of it is yes, but the questions remain: is it possible to be creative within the regulations, and what do the current regulations implicitly prohibit?

The regulations impose a limit on the combined use of CFD and wind tunnel time must fall below a limit line. The natural implication of this is that, for most teams, CFD use is compromised to an extent in favour of wind tunnel time, given that it remains the primary development tool of the teams.

It follows then that one of the most desirable attributes for a CFD simulation is fast turnaround. This has led to a great deal of convergence of methodology between teams to using commercial Reynolds averaged Navier Stokes (RANS) solvers with wall modelling, high under-relaxation factors and high-quality meshes capable of producing steady values of lift and drag within a few hundred iterations.

While this methodology can produce well-correlated results in a timely fashion, however, it does not represent the forefront of development in CFD methodology, and arguably shows that teams are heading towards a stagnation in accuracy improvements. Practicality governs the use of this methodology but the regulations prohibit more accurate and more computationally expensive methodologies. Now let’s examine the possibilities the teams are dissuaded from pursuing.

First, if we discount methods such as direct numerical simulation, large eddy simulation and (to an extent) detached eddy simulation as being impractical – particularly in terms of providing a result within an acceptable timeframe for a Formula One team – then we are still left with main ways of simulating the unsteady flows characterised by a Formula One car: the unsteady RANS and Lattice-Boltzmann methods.

Both provide a wealth of data beyond steady-state RANS solvers, as the ability to look at transient data makes it is easier to visualise how flow structures interact with one another and how vortices generated at the front of the car propagate downstream. Both are available in existing commercial software, the Lattice-Boltzmann method in particular allowing transient data to be obtained at a relatively low computational cost, and because it is inherently transient and has greater numerical stability, it is harder to make the simulation crash. These methods could realistically be used by Formula One teams on a daily basis to drive development; it is primarily the regulations that stop them exploring them further.

Aside from using new methods, teams are equally restricted in trying to maximise the information they can generate in conjunction with their existing RANS solvers. In recent years there has been more emphasis on creating aero-elastic bodywork, which allows teams to set up their car with minimum compromise or (depending on your opinion) completely flout the regulations. Rightly or wrongly, aero-elastic bodywork is an area of interest to Formula One teams, and much of the focus on it has concerned the front wings, specifically flexing the wing to move the ends closer to the floor to further exploit the ground effect or to place the wing into a stall condition to reduce drag.

Aero-elasticity is particularly difficult to model in a wind tunnel: the materials used and the size of the (scale) models are different from the car they mimic, and hence behave differently. Computationally it is possible to model aero-elasticity, although at present it invariably involves coupling a fluid dynamics solver with a structural solver. This presents its own difficulties: scripting is needed to couple the solvers, as is potentially the need to re-mesh the geometry after it has altered shape and skewed some elements. Naturally though, the passing of information between solvers and the need to run longer to achieve convergence for each iteration of geometry change means this is not currently an attractive way for Formula One teams to run their solvers on a daily basis.

It is often said by technical writers that the wheels and tyres account for around a third of the drag on a Formula One car, so modelling the flow interaction with the wheels is seen as crucial to being able to engineer an efficient car. There are currently two main ways of modelling wheel rotation – using a moving reference frame, and using a sliding mesh. The former is the norm for Formula One teams, and relies on assigning a constant speed of rotation to a volume region. The latter is generally out of reach to teams as it invariably requires a transient simulation to be run, although neglecting its use means teams are not modelling the true rotation of the wheel.

Aside from modelling the rotation, another key area teams seek to optimise to improve their correlation is the squash shape of the tyre. Modelling the deformation of the tyre would again involve coupling the simulation with a structural solver, and is hence not possible within the framework of the regulations. So while teams model different trajectories of yaw, steer, roll and ride heights, their accuracy is limited by their grasp of tyre squash.

Next edition’s article on this keyword will continue to examine what the current regulations implicitly prohibit, focusing predominantly on thermal applications.

Written by Sam Wakelam