Engineering and AI with CADFEM/Ansys

Tuesday 10 Nov 2026, 09:00 → 15:00 Europe/Berlin

Online

Matthias Läuter (Zuse Institute Berlin), Patrick Höhn (GWDG)

NHR@ZIB and NHR-Nord@Göttingen are two of nine centers in the NHR alliance. The compute resources in Berlin and in Göttingen support the research community in Germany, especially in the field of computational engineering. The advances in AI offer improvements for engineering software and its applications. Both NHR centers collaborate with the company CADFEM. The presentations will give an overview to interfaces between AI and the engineering software Ansys. Examples on both compute systems will be presented.

Highlights

Discover how AI is transforming engineering simulation.

1. PyAnsys in practice: automating and accelerating simulation workflows with Python
2. Trustworthy AI: how embracing uncertainty turns AI into a reliable partner for engineering decisions
3. Live demos: running Ansys and Fluent jobs on the HPC clusters in Berlin and Göttingen

 

This event is online-only and will be held using a zoom meeting. All registered participants receive the session link via email the day before the event starts.

This course is available for members of German universities or publicly-funded research institutions in Germany. Please register the course using your university/institution e-mail address.

Speakers and Organizers

• Dr. Patrick Höhn (Gesellschaft für wissenschaftliche Datenverarbeitung mbH Göttingen)
• Dr. Matthias Läuter (Zuse Institute Berlin)
• Aileen Lützke (CADFEM)
• Dr. Alexander Seidel (CADFEM)
• Bettina Spiegel (CADFEM)
• Dr. Lewin Stein (Zuse Institute Berlin)

09:00 → 09:10 Welcome

Speakers: Matthias Läuter (Zuse Institute Berlin), Patrick Höhn (GWDG)

09:10 → 10:40 Accelerating Engineering with Python-Driven Simulation

Engineering teams are under increasing pressure to deliver results faster while maintaining confidence in their simulation processes. PyAnsys provides a modern, Python-native ecosystem that helps automate workflows, improve reproducibility, and connect simulation data across tools and disciplines. Using practical examples from multiple physics domains, this presentation shows how PyAnsys enables more efficient engineering processes and lays the groundwork for AI-powered applications by generating the high-quality data they depend on.

Speaker: Aileen Lützke (CADFEM)

10:40 → 10:50 Break

10:50 → 12:20 How Embracing Uncertainty Builds Trust in AI

AI promises faster engineering decisions, but can engineers trust the results? This presentation shows how embracing uncertainty transforms AI from a black box into a trusted partner for simulation-driven engineering. A real-world example highlights not only theoretical but practical benefits of tools already available today.

Speaker: Alexander Seidel (CADFEM)

12:20 → 13:15 Lunch break

13:15 → 13:35 Onboarding and how to use Ansys at NHR@ZIB

Speaker: Lewin Stein (Zuse Institute Berlin)

13:35 → 14:05 Demo how to start a minimal Fluent job on a HPC cluster (without GUI)

Speaker: Lewin Stein (Zuse Institute Berlin)

14:05 → 14:20 Gettting Started with ANSYS at Göttingen

Speaker: Patrick Höhn (GWDG)

14:20 → 14:55 Running ANSYS on the cluster using RSM

Speaker: Patrick Höhn (GWDG)