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<\/p>\n\u2022\tIBM and Dallara are collaborating on the development of new physics-based AI foundation models. <\/p>\n
\u2022\tOne early model was trained on Dallara\u2019s proprietary and validated aerodynamic data of a high-performance vehicle. <\/p>\n
\u2022\tEarly results show the potential to reduce aerodynamics simulation time from many hours to few minutes and help engineers explore more design options earlier in vehicle development. <\/p>\n
\u2022\tThe companies are starting to explore how to integrate quantum computing in the design workflow and further boost simulation fidelity for complex aerodynamic problems. <\/p>\n
Apr 30, 2026<\/p>\n
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PARMA, ITALY & NEW YORK, APRIL 30, 2026 \u2013 IBM (NYSE: IBM<\/a>) and the Dallara Group, a world-leading racing and high-performance vehicle manufacturer, today announced a collaboration to advance vehicle design and optimization using AI and explore the use of quantum computing. The work combines Dallara\u2019s expertise in high-performance vehicle engineering with IBM\u2019s leadership in AI for physics and quantum computing to investigate how to accelerate aerodynamic design and open a path to even more advanced simulation workflows.<\/p>\n For more than 50 years, Dallara has designed and supplied high-performance vehicles for some of the world\u2019s top racing series, including IndyCar \u2014 where track speeds can average more than 230 mph (370 km\/h) \u2014 as well as Formula 2, Formula 3, Super Formula, and Indy NXT, with additional work in top-tier series such as Formula E, WEC, and IMSA. This breadth of racing programs provides a unique ability to validate simulation results against real-world vehicle performance. Dallara also applies its engineering to high-performance road vehicles and aerospace. These and other distinctive, innovation-driven features of the company were key in IBM choosing to collaborate with Dallara.<\/p>\n As part of the project, IBM has been developing domain-specific foundation models in close coordination with Dallara. The models leverage not only Dallara\u2019s high-fidelity aerodynamic simulation data but also the company\u2019s deep technical expertise. In a future step, the teams aim to integrate validated measurements of real vehicles in wind tunnels and on the track, but the use of high-quality simulation data alone is already producing compelling early results.<\/p>\n Engineers rely heavily on computational fluid dynamics (CFD), to predict aerodynamic forces and optimize how vehicles perform across components such as body geometry, underfloor, wings, and wheels. These simulations are powerful but computationally expensive. Even relatively narrow analyses may take a couple of hours or more, while full race car development workflows may take weeks or months as engineers iterate through geometry changes, operating conditions, and performance tradeoffs.<\/p>\n IBM and Dallara are using AI to speed up those workflows without replacing the underlying physics. In one early example, which focused on the geometry of a conceptual Le Mans Prototype 2 (LMP2)-like race car, the two companies jointly compared CFD analyses of multiple configurations of the rear diffuser \u2014 a part located in the rear underfloor that helps generate efficient downforce and thus grip \u2014 with results from the new physics-based AI method.<\/p>\n The traditional approach took a few hours to calculate all the configurations. Meanwhile, the AI model completed the same evaluations in about 10 seconds, identifying the same optimal design with roughly the same error margins as CFD. Applied to a typical complete set of hundreds of geometry configurations, such a speedup could cut days of simulation time down to minutes.<\/p>\n These and other preliminary results suggest Dallara engineers can evaluate more vehicle configurations in a fraction of time to move faster in early design phases, helping focus their most expensive computational resources on deep-dive optimization of race car design and development.<\/p>\n In early pressure-field modeling of adjusting an LMP2-like race car\u2019s rear diffuser angle from -2 to +4 degrees, results from typical CFD (left) and the new IBM physics-based AI approach (right) were remarkably close. Credit: IBM & Dallara.<\/p>\n In parallel, IBM and Dallara are starting to explore how quantum and hybrid quantum-classical approaches could further enhance race car design workflows. By combining Dallara\u2019s expertise in high-fidelity vehicle engineering and CFD-driven design with IBM\u2019s leadership in quantum computing and AI, the collaboration will evaluate where these methods can complement traditional simulation workflows in the near-term while identifying longer-term opportunities for practical use in automotive and motorsport design.<\/p>\n \u201cRacing has taught Dallara that there are two possible outcomes: you either win or are forced to learn. IBM\u2019s close collaboration on this innovative project is a testament of Dallara\u2019s willingness to continuously push its boundaries and never stop learning,\u201d said Andrea Pontremoli, Dallara CEO.<\/p>\n \u201cSome of the hardest engineering challenges come down to accurately simulating the physical world,\u201d said Alessandro Curioni, IBM Fellow and VP, Algorithms and Applications, IBM Research. \u201cWith Dallara, IBM is applying AI to speed up aerodynamic design today while advancing quantum computing in parallel to push simulation farther. Together, these technologies can help engineers move faster, explore more possibilities, and ultimately design better-performing vehicles.\u201d<\/p>\n Advancing aerodynamic design with AI<\/p>\n Designing a high-performance vehicle means balancing downforce, drag, stability, and responsiveness across conditions that can change from race to race. Because some parts are designed with exacting precision, even small design changes can lead to surprisingly large impacts on performance, and the best aerodynamic solution is not always obvious.<\/p>\n The AI models are being designed to help predict aerodynamic behaviors directly from geometry and related engineering inputs. As the collaboration progresses, IBM and Dallara plan to expand the AI models across a wider range of conditions, such as different maneuvers or overtaking scenarios, apply them to design new vehicles and develop tools that enable faster exploration of new aerodynamic configurations, before investing in intensive full-vehicle simulations.<\/p>\n \u201cHigh-performance vehicles are an ideal proving ground for neural surrogate models, but the potential impact goes well beyond the racetrack,\u201d said Fabrizio Arbucci, Dallara CIO. \u201cMore efficient designs could benefit all transport categories, from passenger vehicles to aircraft, and even other industries at the mercy of aerodynamics. Even a one to two percent reduction in drag across passenger vehicles could add up to meaningful fuel-efficiency gains at scale.\u201d<\/p>\n Initial results of the collaboration are detailed in a preprint study<\/a> published at arXiv on April 20, 2026. This work builds upon a new AI model developed by IBM, called Gauge-Invariant Spectral Transformers (GIST), which was described in a March 17th preprint study<\/a>. IBM and Dallara presented these and other advances in applying AI to complex physical systems on April 26, 2026, at the International Conference on Learning Representations in Rio de Janeiro.<\/p>\n About IBM<\/p>\n IBM is a leading provider of global hybrid cloud and AI, and consulting expertise. IBM helps clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Thousands of governments and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM’s hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM’s breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and consulting deliver open and flexible options to our clients. All of this is backed by IBM’s long-standing commitment to trust, transparency, responsibility, inclusivity and service. Visit www.ibm.com<\/a> for more information.<\/p>\n About The Dallara Group<\/p>\n Founded in 1972 by Giampaolo Dallara, Dallara is a world-leading manufacturer specializing in the design, engineering, and production of racing cars for top-tier motorsports. The firm has expanded globally from Italy’s Motor Valley with a US Dallara Experience Hub in Speedway, Indiana. Dallara is the sole builder of racing cars for the IndyCar, Indy NXT, Formula 2, Formula 3 and Super Formula Championships, it also supplies Cadillac and BMW in both the WEC and IMSA championships. The expertise acquired in racing is regularly used both in the automotive world through consultancies and production services, with also Dallara branded products like the Dallara Stradale and DallaraEXP and more recently in aerospace. Visit www.dallara.it<\/a> for more information.<\/p>\n \u00a0<\/p>\n Media Contacts<\/p>\n IBM Research Ashley Peterson<\/p>\n
\nDave Mosher
\nIBM Research Communications
\ndave.mosher@ibm.com<\/a><\/p>\n
\nIBM Research Communications
\nashley.peterson@ibm.com<\/a><\/p>\n