Browse Publications Technical Papers 2020-01-0665

Towards High-Fidelity CFD on the Cloud for the Automotive and Motorsport sectors 2020-01-0665

Computational Fluid Dynamics (CFD) is at the heart of the Formula 1 aerodynamic design process. Compared to wind-tunnel experiments it offers a much quicker and cheaper way to assess new designs and provides greater information on the complex unsteady flow physics around the vehicle. The use and trust in CFD has grown, thanks largely to the increased availability of High-Performance Computing (HPC) resources, however the number of concurrent simulations mean that these simulations are typically done using steady Reynolds-Averaged Navier-Stokes (RANS) based CFD methods that have been shown to compromise accuracy for speed. Hybrid RANS-LES simulations have been shown to offer much greater accuracy due to the reduced modelling and the ability to capture the unsteady flow physics that are present in the wake of the tyres and the body itself. In this work, we discuss the work done to enable the use of overnight hybrid RANS-LES simulations (Detached Eddy Simulation family in this paper) using more than 400 million cells on the Amazon Web Services (AWS ) platform to aid the 2021 overtaking group at Formula 1 Management. We discuss the extensive benchmarking that was undertaken both on a platform level (hardware & middleware) and the methodology choices within the OpenFOAM CFD code. The result is a set of best-practices for other automotive and motorsport companies wishing to running large-scale hybrid RANS-LES simulations on the AWS platform using OpenFOAM or similar CFD codes.


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