F1 Aerodynamics: Pressure-Based Vs. Density-Based

F1 Aerodynamics CFD Simulation, Pressure-Based and Density-Based

Description

This project examines the aerodynamic coefficients of a Formula One (F1) car using two distinct solver approaches — pressure-based and density-based — at a speed of 111 m/s with zero lateral angle (representing straight-line travel).

At ground level, this velocity corresponds to a Mach number of approximately 0.32, placing the flow within the transition zone between incompressible and compressible behavior. Given this borderline regime, the drag coefficient was investigated using both solver types to compare their performance and accuracy on this geometry.

Since flow characteristics also influence the upstream region in subsonic flow, the computational domain was sized generously upstream. Downstream, the domain was similarly extended to properly capture the wake vortices shed behind the geometry, supporting convergence in the larger computational domain.

The geometry was modeled in Design Modeler, with elements generated in ANSYS Meshing using a polyhedral mesh totaling 1,253,296 elements.

Methodology

The problem was solved under steady-state conditions using both pressure-based and density-based solvers, with turbulence modeled using the Realizable k-epsilon model in both cases.

Conclusion

Convergence was assessed by monitoring the iterative solution and confirming residuals reached the defined convergence criteria, with particular attention paid to the convergence behavior of drag force — a stable, non-fluctuating value in this quantity indicating a converged numerical solution.

The drag force results are broadly comparable between the two solver types, indicating that for this Mach number and geometry, the density-based solver's compressible-flow handling did not introduce dramatically different results. The key distinction lies in computational efficiency: the pressure-based solver converged in fewer iterations, making it more time-efficient.

Given its lower computational cost alongside reasonably accurate results compared to the density-based approach, the pressure-based solver is identified as the more appropriate choice for this particular simulation case.