Tech insight: CFD design in the 488 GTE
WEC

Tech insight: CFD design in the 488 GTE

Maranello | 7 May 2020

Speed is a crucial ingredient for final success in the world of competition. Just as it is essential on the track, during pit stops, it also plays a vital role in the design phase. It allows us to evaluate more scenarios in the concept phases for faster development of solutions to be used during a race.

Feverish activity takes place at circuits around the world and in the technical department of Ferrari Competizioni GT which analyses and studies the requests and feedback received from drivers and engineers to implement changes that can yield a competitive advantage or boost a car’s reliability. Whether a design starts from a blank sheet of paper or evolves an existing vehicle, the world of virtual simulation plays an increasingly important and decisive role. It enables a significant reduction in development time and costs, and the testing of multiple solutions and configurations.

Since 1998 Ferrari has used Ansys to provide cutting-edge simulation solutions for the design and development of its GT racing cars, such as the 488 GTE. When studying aerodynamic configuration, for example, computational fluid dynamics (CFD) software lets Prancing Horse engineers use a 3D model to test their modifications before moving on to the wind tunnel. These models provide highly accurate simulations of all the flows to which the car body is subject, and even simulate energy exchanges and determine heat and temperature transfers of components.

With the support of the US company’s developers, Ferrari engineers used Mosaic enabled Poly-Hexcore meshing technology to cut the number of cells by 15%. This reduction, combined with the innovative hexahedral-dominant mesh, slashes overall solve times by half. The Ferrari team can now run 300% more CFD simulations, helping the engineers to develop their cars or new solutions faster.

The continuous refinement of these physical and mathematical models produced by Ansys’s developers has allowed us to achieve great rapidity of execution and extremely high levels of correlation with the experimental data. It has also enabled us to widen the field of simulations to conditions and flows to types of conditions that are ever more representative of the car on track during races with absolute precision, responding even more quickly to requests from teams and drivers. All this shows, once again, how speed, in all fields, is a key factor for success.