Hydroplaning or aquaplaning

An efficient tire must meet multiple objectives, including fuel consumption, durability, shock and cut resistance, rolling noise, grip on dry or wet roads, aquaplaning prevention… Many of these constraints involve complex physics and, for the most part, entail contradictory compromises.

Your application

Among the numerous design constraints, aquaplaning directly involves fluid structure interaction. Understanding the actual dynamics is not easy. Indeed, the flow beneath the tire and inside its grooves cannot simply be observed or measured, with good reproducibility and reliability. Even if it could, such experiments for designing new tires would imply expensive prototypes and on-track testing facilities. Such financial and time constraints would prevent designers from assessing numerous innovative concepts.

Another major concern for car, truck or aircraft designers involves splashing when tires roll through water. In the automotive industry, manufacturers want to make sure the car, and more specifically the door handle, is not systematically covered with mud after each rainy-day ride, which would drastically deteriorate the user experience. In the aeronautics industry, the issue is safety: during take-off or landing on a water-logged runway or carrier, any misdirected water splatter could cause dramatic water ingress in the aircraft’s engine.

Our solution

Drawing on many years of aquaplaning-related experience with the tire manufacturer Michelin, we have constantly tried out and improved the SPH-flow solver.

We have developed a long-term expertise with Michelin on the use of the SPH-flow solver that provides the following advantages in the context of hydroplaning simulations:

  • Easy and fast set-up
  • Possible to measure global effort and local pressure map (on the tire and on the road)
  • Only fluid phase can be simulated
  • Efficient for splash
  • FSI: coupling with proprietary and commercial FEM codes (3DS SIMULIA Abaqus, EDF Code_Aster)
  • Optimized for HPC: scalability on a high number of cores, local refinement, reasonable simulation times

Solvers

Customers /  Partners

Collaborative Research Project