The DrivAerNet++ database was compiled from 39 terabytes of data and over 8,000 3D models based on existing car designs, allowing advanced AI training.
The dataset aims to train AI models in optimizing combinations of features while reducing research and development costs and accelerating car design processes.
Faez Ahmed emphasized that larger datasets with detailed performance metrics allow for more substantial design innovations rather than just marginal tweaks.
By understanding fluid dynamics and aerodynamics through simulations, manufacturers can significantly enhance electric vehicle designs, creating better-performing and more efficient cars.
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