Driven by Simulation, a Regulations Overhaul Promises a New Era of Racing in Formula 1

HPC and simulation are at the core of the new F1 rules and the ability of teams to innovate within the tight restrictions.

After a tumultuous end to the 2021 season, fans and racing teams alike are looking forward to the next era of Formula 1 (F1) racing being ushered in for 2022. A regulations overhaul set forth by F1 and the FIA is promising improved racing and a tighter field for the upcoming season. Since 2017, the FIA and F1 have redesigned the aerodynamic regulations to help cars more closely follow one another and improve wheel-to-wheel racing.

In 2021, F1 also introduced a cost cap to help tighten up the grid and provide a more level playing field. Within the cost cap, limits on wind tunnel testing and computational fluid dynamics (CFD) simulations were introduced to help teams with smaller budgets remain competitive. Now, between the ongoing pandemic limiting wind tunnel time and extensive changes to the aerodynamic rules, teams are relying even more heavily on CFD and other simulation software to support their vehicle designs and real-time decision-making.

An image of the model 2022 F1 car, including major changes to the front and rear wings as well as new wheel covers and over-wheel winglets. (Image courtesy of Formula 1.)

An engineer simulating an F1 car. (Image courtesy of  Ansys.)

With closer racing, the upcoming season promises to be exciting for both fans and drivers. How teams will innovate within the new aerodynamic regulations remains to be determined, with most F1 teams slated to debut their new car designs over the next two months.

F1 Used CFD Run on AWS High Performance Computing to Develop 2022 Regulations

The 2022 regulations were designed collaboratively by F1’s in-house motorsport team and the FIA. The goal was to produce cars that could meet the cost cap while reducing turbulence and improving racing. The process began in 2017 and a mock-up was revealed in July 2021.

Initially, F1 set out to understand why it is so challenging for current cars to follow one another on the track. Using CAD data from the previous Manor Formula 1 team, F1 ran CFD simulations of the wake generated by a car during driving. The initial simulations were compared to Sauber wind tunnel data to confirm their validity.

With a working model, F1 could then launch into a simulation program to develop a set of regulations that would improve the ability of cars to follow one another. F1 partnered with Amazon Web Services (AWS) to run its CFD simulations on the Amazon Elastic Compute Cloud, an HPC platform. The development process required 1,150 computer cores and generated nearly 550 million data points for each model run through the software. With about 7,500 simulations run since 2017, F1 notes that its CFD simulations required 16.5 million core hours of computing, which would take a 4-core laptop 471 years to complete.

The resulting design reduces the turbulent air created by a car and reduces a vehicle’s sensitivity to following in the generated wake. CFD demonstrated that the following vehicle could maintain about 86 percent of its downforce when it was one car length away, compared to current cars that can only retain about 55 percent of their downforce. In the past, this reduction in downforce made it difficult and even dangerous to follow behind and ultimately pass other cars. Easier following with the new aerodynamic regulations will hopefully provide more competitive racing and a tighter field across the 20 F1 teams.

So, how did F1 and the FIA generate the new design? Through careful consideration of how the downforce is generated and how the turbulent air created by a car can be streamlined to reduce wake. Following the CFD simulation program and wind tunnel testing, the regulations now include over-wheel winglets and wheel covers to reduce the amount of wake generated by open wheels. Previously, disruptive airflow was released through the wheel openings to help increase the downforce. The new regulations will prevent the chaotic release of airflow that disrupts cars following closely behind another vehicle.

Beyond the wheels, a new front wing design will help create consistent downforce while a car is following behind another vehicle. Plus, the rolled tips of the rear wing will prevent airflow from being pushed directly into following vehicles. Instead, the new design of the rear wing will collect the rear wheel wake and the air leaving the diffuser and push it upward. As a result, cars can now follow the front vehicle more closely with the wake being pushed up and over oncoming vehicles.

The 2022 regulations also feature improvements to safety and a switch to more sustainable fuel, with F1 still aiming to adopt a net-zero carbon footprint by 2030.

The Ongoing Partnership Between Ansys and Red Bull Racing Honda: CFD and Beyond

Red Bull Racing has made a big splash in F1 racing, winning numerousWorld Championships and adding another World Driver Championship to its legacy in 2021. In terms of software, one of the longest and most successful partnerships in F1 is between Red Bull Racing and Ansys. The F1 team has partnered with Ansys since 2008, using Fluent CFD software to support simulation efforts and iterative car design.

Initially, Red Bull partnered with Ansys for aerodynamics simulation and has since expanded to using the company’s suite of software solutions to solve cooling issues, optimize material usage, and improve vehicle safety.

With the introduction of the cost cap and limits on CFD simulations, the Red Bull team works closely with Ansys to optimize efficiency and use Fluent meshing for all preprocessing. Fluent is also used to design a car’s cooling capabilities and prevent overheating from the power unit. The software automates every part of the process so that an engineer can set up a simulation and let it run, simply analyzing the results when they are ready. Red Bull says that it uses Fluent over other common CFD software such as Simcenter STAR-CCM+ due to its industry-leading speed and accuracy. With changes to a race vehicle often needed in less than a week, time and efficiency are critical for any F1 team.

(Image courtesy of Ansys.)

The fruits of Red Bull Racing Honda’s hard work on and off the track. (Image courtesy of Ansys.)

“By working closely with Ansys, we get access to their developers to discuss problems, guide development of the tools, get advice from them as to how to better use the tools, and to give them ideas for their development as well,” said Matthew Sorrell, head of Aerodynamics Tools and Methods at Red Bull Racing Honda. “We get access to beta test features to test but also to make sure it works on our applications. In many ways we are specialists and we’re hopefully pushing the limits of the technology beyond the average user. We’ve found that the partnership has been mutually beneficial over the years.”

But the F1 team doesn’t just leverage Ansys Fluent, it also uses LS-DYNA to run simulation-based crash testing. The software reduces the costs and time typically required for physical crash testing to accelerate the design of safer vehicles.

“We continue to benchmark to ensure we are using the best-in-class tools and are confident working with Ansys ensures we stay ahead of the game,” said Matt Cadieux, CIO at Red Bull Racing Honda. “By integrating Ansys’ technology into our design processes, our team iterates designs much faster, giving us the edge against our competition on the track.”

Mercedes-AMG Petronas Looks to Stay Ahead with Digital Twins and TIBCO Data Analytics

Another example of simulation technology in F1 is the story of Mercedes-AMG Petronas partnering with Tibco for both advanced data analytics and digital twin simulations. With race simulators, F1 teams can replicate real-world track conditions to test a variety of factors that may impact performance on race day. For example, simulators can modulate everything from seat adjustment to on-the-track sounds and conditions.

But the main benefit from the simulator is its digital twin, the virtual software replica of the race car that generates data based on modifications made to the race setup. Mercedes uses TIBCO Spotfire and Data Science software to monitor data generated by the digital twin, visualize results, and determine which setups will give the team a cutting edge on race day.

“Simulations are very dynamic; they’re not a static thing where you leave the factory and then just land at the track. They cover things like the suspension and potential wind effects, and those setups are constantly tweaked at the garage, in transit, and at the circuit—back and forth,” said TIBCO Chief Analytics Officer Michael O’Connell.

TIBCO is also supporting Mercedes with a Cost Visualizer Tool (CVT) to help them meet the new cost cap. The engineering, finance and operations teams at Mercedes worked together to determine where time and money were being spent. After every race, the CVT is run to identify cost drivers and ensure that the team remains within the new budget requirements.

How Do F1 Teams Pick Their CFD Software?

With CFD software, many F1 teams keep their choice a trade secret. Except for Red Bull Racing Honda, many teams do not openly discuss their choice in CFD software or even their advanced data analytics. Most teams will talk only about technology sponsorships displayed as part of their livery and attempt to keep their software details under wraps.

Through discussions with previous engineers and aerodynamics experts, it comes as no surprise that most teams use either Ansys Fluent, Siemens Simcenter STAR-CCM+, OpenFOAM and/or proprietary software for CFD simulations.

Compared to other software, some have said that Fluent can take less time to set up a simulation case, reducing the time to generate a result—an important factor for industries like F1 where time is critical. But, of course, this comes at a price, as opposed to open-source options like OpenFOAM.

Ultimately, each software can run advanced CFD simulations. The selection may come down to the personal preference of the engineering team or individual sponsorships. Many teams actually differentiate their CFD simulation capabilities by expanding HPC on-premises or cloud infrastructure to simply support more parallelized simulations. With more data, teams can glean further insights into the best setup for vehicles, which can be customized to each track on the F1 calendar. Plus, teams can further differentiate themselves through different advanced data analytics to sort through massive amounts of CFD data.

The Era of the Software Car Is Here

From classical CFD to digital twins and race simulators, the software era of F1 is here. With the introduction of the cost cap and the complications of the COVID-19 pandemic, teams are relying more heavily on simulation to support car design and race day decisions. Simulation goes hand in hand with advanced data analytics, and software now provides F1 teams with their competitive edge. With thousandths of a second often determining who will take the coveted pole position during qualifying, minute differences in vehicle design and customizations to suit individual track conditions are necessary to succeed in a tight field.

As we’ve seen in the past, innovation at the highest level of motorsport ultimately influences vehicle design for consumers. As F1 continues to push the boundaries of simulation and software usage for vehicle design and operation, the entire automotive industry will soon gain similar benefits that will impact our everyday lives.

The 2022 season will be an exciting time for F1 fans. With F1 racing being an engineering competition as much as a racing contest, it will be interesting to witness how each of the teams interprets the new regulations and continues to use CFD to support their iterative design processes.