AI-driven simulation technologies are increasingly promoted as a potential “holy grail” for the automotive engineering community, promising accelerated vehicle development and breakthrough design capabilities. Nonetheless, important questions remain around topics such as:
- The extent to which machine learning solvers can already deliver reliable, swift, and well-reasoned design decisions.
- The inherent drawbacks and risks of data-driven simulation methods.
- The challenges which must be addressed to enable large-scale implementation of machine learning solvers in safety-critical automotive engineering.
- How geometry-aware machine learning methods can transform design and simulation, and which obstacles still limit their practical adoption.
This webinar presents the main takeaways from the work of the FISITA Digitalisation Expert Group, along with key success stories showcasing different applications of AI in simulation, including:
- Real-time prediction
- Predictive simulation
- Support for model generation
These topics have been explored by the FISITA Digitalisation Expert Group, whose White Paper, on AI for CAE consolidates the findings by reviewing the current state of the technology, assessing the feasibility of its rapid integration into vehicle development, and projecting its potential for broader adoption across the automotive industry.
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