Rune Aero has revolutionized its aircraft development process using an interactive virtual wind tunnel that’s driven by AI of physics, which reduces a discount in early construction costs by 80%, the payload capability has doubled and reduced fuel consumption by 50%.
The groundbreaking digital Twin technology combines Luminary Clouds Nvidia Cudax-Akhelations -CfD simulations with one Nvidia omniverse Blueprint for Real time computer -aided technical digital twins in real time. Ultimately, engineers can observe aerodynamic effects immediately if they alter designs. This transformative approach has compressed, which traditionally requires months of iterative physical tests right into a continuous real-time optimization process for the autonomous startup of freight aircraft.
The company announced the announcement at NVIDIA GTC 2025 in San Jose, California.
AI physics transforms the aircraft economy with real-time design optimization
Rune Aero was founded in 2023 and developed a sustainable and autonomous aircraft for the growing marketplace for the center mile. As a brand new startup, they include Physics AI, a contemporary approach to quick design exploration. Rune Aero's introduction of the virtual wind tunnel shows how engineers from Aerospace Design quickly analyze many prototypes of aircraft design, ittery and visualize the results in real time.
By performing virtual wind tunnel tests within the design process, Rune Aero reduces the longer term technical risk and the prices dramatically compared to traditional physical wind tunnel tests.
The company said the outcomes were transformative: 70% reduction in operating costs for freight operators through optimized aerodynamics and fuel efficiency, doubled payload capability and 50% lower fuel consumption. For the operators, this results in a double -digit profitability increase that fundamentally change the air freight economy.
Luminary Cloud developed the interactive virtual wind tunnel by combining its GPU native CFD solvers, the NVIDIA CUDA-X libraries, the physicsnemo-AI training framework and the omniversu visualization API to create digital twin environments that provide immediate design feedback. This technology stack enables other digital twin environments to incorporate real data within the physics AI platform.
“AI-Physics models are essential for the evaluation and design of the interactive technology in real time, but require enormous amounts of information,” said Tim Costa, Senior Director Cae EDA and Quantum at Nvidia in an evidence. “The accelerated CFD solver from Luminary Cloud enables customers to generate the info required for the training of the AI Physics Model in Nvidia Physicsnemo in Nvidia Physicsnemo in just a few hours.”
“It is exciting to work with aerospace firms comparable to Rune Aero which can be able to use latest design optimization techniques. By quickly executing a big database with simulations and creating physics -ai models, Rune Aero engineers can get a practical design faster to resolve vital regional air transport problems,” said Juan J. Alonso, CTO Luminary Cloud.
“In the early stages of aircraft development, the feedback of faster, precise and cheap design is of essential importance. The virtual wind tunnel from Luminary enables Rune Aero to check earlier, with our early development costs in comparison with traditional wind tunnels and a fömer murder of smart design decisions by over 80%.” Aircraft configuration of rune, which ends from these tests, improves the aerodynamic lift to pull ratio together with advanced drive, which doubles payload and range, whereby the fuel reduces 50%and ultimately reduces operating costs for our customers. ”
Luminary Cloud and Ntop also announced a brand new integration with Nvidia Physicsnemo, which reduces physical AI design optimization from weeks or months to only hours. Due to the seamless connection of NTOPS parametric geometry generation, GPU native simulation and simulation management platform from Luminary and Nvidia Physicsnemo via NIM-Microservices, the engineers can now create a whole lot of draft fluctuations in in the future and analyzing a process for months Systems were tasted.
