BeyondMath’s AI ‘Digital Wind Tunnel’ Speeds Up F1 Car Design

Simulating real-world physics is a complex challenge, especially at the high fidelity needed for industries like automotive and aerospace. Traditional techniques often slow down design teams, but BeyondMath is leveraging AI to offer a faster, more efficient solution that could save valuable time in the design process.

The Challenge of Computational Fluid Dynamics (CFD)

Computational fluid dynamics (CFD) has long been a cornerstone in the design process for vehicles, aircraft, and other complex systems. These simulations, which model how air or water flows around objects, require immense computational power and often lead to significant delays. Designers typically run simulations overnight, only to find that results may require them to start the process over again, adding days or even weeks to development timelines.

Darren Garvey, co-founder of BeyondMath, highlighted the limitations of traditional CFD methods: “For a designer, they put a lot of thought into what might work, then they run a simulation. Then they come in the next morning and they’ve got the results. Either it did what they wanted or not, and they have to go through this loop a few more times. Then you take it to the wind tunnel,” and the wind tunnel may well not agree with the simulation, so it’s back to the drawing board.

BeyondMath's AI-Driven Solution

BeyondMath aims to accelerate the digital design process with its new AI-powered "digital wind tunnel." This tool provides near-real-time simulations of airflow over complex surfaces, delivering results that traditionally would take much longer to compute. By integrating machine learning with physical models, BeyondMath offers a way to drastically increase the efficiency of the design iteration process.

Unlike other AI applications that rely on vast amounts of training data, BeyondMath’s model combines theoretical physics with real-world data to simulate the actual behavior of systems. “We’re not trying to approximate the simulations, we’re trying to approximate the real world,” Garvey said. “And you have to bring in real-world data to do that.”

First Applications in Formula 1 Racing

BeyondMath’s initial market focus is on Formula 1 racing, where teams are known for their heavy reliance on CFD to optimize vehicle aerodynamics. Several F1 teams are already testing BeyondMath’s software to accelerate their design processes. Garvey is optimistic about the impact, stating, “We’re close to having a platform that will actually make their cars faster.”

Within six months, the company hopes to demonstrate tangible benefits for their customers, transitioning from research and proof-of-concept stages to real-world applications that improve performance on the track.

Scaling Up and Looking Ahead

To support its growth, BeyondMath recently secured $8.5 million in seed funding, led by UP.Partners with participation from Insight Partners and InMotion Ventures. The company plans to double its team size and expand its computational capabilities, including acquiring Nvidia DGX 200 systems to further enhance their AI models.

While Formula 1 is a key early market, BeyondMath is also considering broader applications. “We’re seeing a lot of success in our customers’ design space, but it’ll be a journey from that to something more generalizable. For example, if a model understands cars, or car-like objects, it’s not necessarily going to understand a plane, or a blood vessel,” Garvey said. The startup's focus on top-tier customers is intended to build a strong foundation before expanding into other industries.