Motor sport has always been at the forefront of innovation in many different areas. Since the early 1900s, the goal to gain a competitive edge has led to some of the greatest inventions in racing that we still use to this day. The first disc brakes allowed Jaguar to win the Le Mans race, Carbon Fiber has replaced aluminum, and semi-automatic gears and paddle shifters are still used today in Formula 1. The active suspension on the 1992 Williams car was so advanced that it was banned from Formula 1, and the original rear-view mirror was used in the first edition of the Indianapolis 500.
In 2022, each motor sport team is still trying to innovate to gain a competitive edge over the competition and at some points just trying to keep up. Building race cars is expensive and over the years, it has been replaced by virtual simulations of different aspects of the cars. The most common simulation is computational fluid dynamics (CFD), which is used for external aerodynamics, internal combustion, and fluids moving inside the powertrain. One of the major goals of any race car is fighting air resistance. The smallest change in geometry has a huge impact on your top speed and the downforce keeping the wheels on the track.
With the high speeds, the cars need to be designed for driver safety, and building and crashing cars is expensive. Running finite element analysis (FEA) allows us to virtually analyze the effect of front, back, or side crashes without any carbon fiber ever being used. A great example is Formula 1: For the 2022 season, the nose of the car needs to absorb 48% more energy, while the rear structure of the car needs to improve by 15%. Red Bull Racing has all the regulation changes for the upcoming season.
Vehicular dynamics doesn’t require as many compute resources, but you need to run thousands, even millions of combinations to understand how the parameters influence the results and interact with each other. Along the same lines, race strategy is the art of using the pits to your advantage, as described in detail in this blog. Using Monte Carlo analysis, you can simulate the race billions of times to decide the optimal method of winning.
Most governing bodies are implementing cost caps to avoid giving unfair advantages to teams with deeper pockets. Planning for the number of simulations running daily is not an easy task. On-premises cluster managers can see large clusters as half-empty (or half-full depending on your mindset) or always-full smaller cluster with large wait times. By running on Oracle Cloud Infrastructure (OCI), the number of cores available is always just right, leaving the cluster managers, purchase team, and engineers happy.
Another issue faced by the motor sport engineers is the type of resources available. Different workloads require different architectures. The list is long: Ampere A1, latest Intel, or AMD generation, GPU computing, high and low memory needs, the need for local NVMe storage, low latency networking needs... The ideal compute setup for each workload is different.
Using OCI, you can always run the most efficient combination to drive down cost and maximize performances. Finally, getting new hardware shipped to on-premises data centers in a short time is becoming more difficult. With OCI, it only takes a few minutes to have the right cluster set up and simulations running
As with any motor sport innovation, it can be used for everyday car. For this reason, the same simulations have been used by many customers at OCI to enhance both security and performances, while keeping the cost of the car down. Nissan and Toyota are great examples of how companies can us OCI to bring safety and quality to their customers.
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I am an HPC Solution Architect for Oracle Cloud. I have a master in Engineering in Applied Mathematics from UCL in Belgium and a master in Applied Physics from Northern Arizona University. I previously worked for Noesis Solutions as an Application Engineer. I live in Boulder and am loving all the outdoor activities it provides.