Accelerating R&D Processes with AI-Driven CAE
With PDTec: how centrally managed simulation data, task-specific AI models and SPDM integration speed up development in the automotive industry.
What we learn on projects we share in trade journals and at conferences of the simulation community.
With PDTec: how centrally managed simulation data, task-specific AI models and SPDM integration speed up development in the automotive industry.
With AUDI: an AI-reduced model sizes charging cables with phase-change material for fast charging, without simulating every variant.
A neural network assesses pipe cross-sections and bends, lowering flow resistance and the energy demand of water generators.
Neural networks predict snap hook stress from geometry, material and boundary conditions, and solve the design task inversely as well.
Phase-change material as passive heat storage during fast charging: FEM study, prototype and an ML model for inverse design.
How a neural network predicts residual wall thickness and returns the process setting for a required thickness.
| Event | Date | Place | Talks |
|---|---|---|---|
| NAFEMS SPDM & AI/ML Conference 2026 | 27–29 October 2026 | Garching near Munich |
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| CONTACT Open World 2026 | 23–24 September 2026 | Bonn |
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| NAFEMS DACH Conference 2026 | 5–7 May 2026 | Bamberg |
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| ESA AI STAR 2025 | 3–5 December 2025 | Darmstadt |
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| Symposium on Disaster Research 2025 | 18–20 September 2025 | Wels |
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| NAFEMS World Congress 2025 | 19–22 May 2025 | Salzburg |
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| VDI SIMVEC 2024 | 19–20 November 2024 | Baden-Baden |
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| CADFEM Conference 2024 | 7 November 2024 | Salzburg |
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| NAFEMS DACH Conference 2024 | 10–12 June 2024 | Bamberg |
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| NAFEMS Nordic Conference 2024 | 22–23 May 2024 | Gothenburg |
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| prostep ivip Symposium 2024 | 10–11 April 2024 | Munich | – |
| NAFEMS Seminar: AI and ML in CAE-based Simulation | 23–24 October 2023 | Munich |
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25–28 April 2027 · Vancouver
Seminars and workshops at your site are available on request at any time.
A guided look at dAIve Predict using your data or a comparable example.
Work out together which data are suitable and what a sensible start looks like.
A talk on AI in engineering for your development department or leadership team.