Date: Mon. November 30, 2026
Event: FAU MoD Lecture
Organized by: FAU MoD, the Research Center for Mathematics of Data at Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)
FAU MoD Lecture: From Process Physics to Predictive Manufacturing: Challenges in Modelling Electron Beam Powder Bed Fusion
Speaker: Dr.-Ing. Matthias Markl
Affiliation: Numerical Simulation Group at the Chair of Materials Science and Engineering for Metals at Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)
Abstract. Electron Beam Powder Bed Fusion (PBF-EB) is a complex additive manufacturing process involving multiple interacting physical phenomena across a wide range of spatial and temporal scales. Understanding the relationships between process parameters, material behaviour and the resulting material properties remains a major challenge, requiring a combination of experimental investigation and physics-based numerical modelling.
This lecture presents the challenges of modelling PBF-EB across different scales, highlighting the capabilities of current simulation approaches as well as their computational demands and limitations. The increasing complexity of the process and the large parameter spaces involved raise fundamental questions about how simulation-based knowledge can be used more efficiently to understand, predict and ultimately design manufacturing processes.
Against this background, the lecture explores potential connections between physics-based modelling, data-driven approaches and mathematical optimisation. Rather than focusing on a particular machine learning method, it discusses the opportunities and open questions involved in combining these approaches, from accelerating computationally expensive simulations to moving towards inverse process design. The aim is to illustrate a challenging application domain in which manufacturing science, computational modelling, applied mathematics and artificial intelligence can complement one another.
OUR SPEAKER
Dr.-Ing. Matthias Markl is the Head of the Numerical Simulation Group at the Chair of Materials Science and Engineering for Metals at Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany. Since 2020, he has also served as Managing Director of the Collaborative Research Center Transregio 103 Superalloy Single Crystals. His research focuses on the numerical simulation of metal additive manufacturing, particularly electron beam powder bed fusion, covering process physics, microstructure evolution, and process optimization. He has authored more than 60 peer-reviewed journal publications and has contributed extensively to the development of simulation methods for powder bed fusion. Dr. Markl is actively involved in organizing international conferences on additive manufacturing and serves as guest editor for several special issues in the field.
AUDIENCE
This is a hybrid event (On-site/online) open to: Public, Students, Postdocs, Professors, Faculty, Alumni and the scientific community all around the world.
WHEN
Mon. November 30, 2026 at 11:00H (Berlin time)
WHERE
On-site / Online
[On-site] Friedrich-Alexander-Universität Erlangen-NürnbergRoom H13. Johann-Radon-Hörsaal
Cauerstraße 11, 91058 Erlangen. Bavaria, Germany
GPS-Koord. Raum: 49.573764N, 11.030028E [Online] https://www.fau.tv/clip/id/64145
Shortlink to share this event: https://go.fau.de/1ebce
You might like:
• FAU MoD Lectures
• Upcoming events
• FAU MoD Courses & Workshops
• FAU/Jilin Workshop: Workshop on Recent Trends in Applied Mathematics and Machine Learning 2026
• FAU MoD Course: Discovery of singularities with physics-informed neural networks by Prof. Dr. Gonzalo Cao-Labora
• FAU MoD Lecture: Moving your robotic hand is a matter of time and practice by Prof. Dr. Claudio Castellini
• FAU MoD Lecture: Trustworthy AI: Reliable, Explainable, Revisable by Prof. Dr. Ute Schmid
• MLPDES26 workshop: MLPDES26, Machine Learning and PDEs Workshop (2026)
• FAU MoD Lecture: Reverse typography and the theory of shape: Can old books be brought back to life? by Prof. Dr. Jean-Michel Morel
• FAU MoD Lecture: A data-driven approach to closed-loop control of wound state progression to drive healing outcomes by Prof. Dr. Marcella M. Gomez
• FAU MoD Lecture: Data Driven Modeling for Scientific Discovery and Digital Twins by Prof. Dr. Dongbin Xiu
• FAU MoD Lecture: A long life: How desirable is it, evolutionarily speaking? by Prof. Dr. Hanna Kokko
• FAU MoD Lecture: Bridging numerics and scientific machine learning for industrial applications by Dr. Christopher Straub
• FAU MoD Workshop: FAU MoD Workshop (Dec. 2025) by Prof. Giovanni Fantuzzi | Prof. Denisa Martonova
• FAU MoD Lecture: Quantum firmware: optimal control for quantum processors by Prof. Dr. Tommaso Calarco
• FAU MoD Lecture: AI Components in PDE Solvers by Prof. Dr. Nils Thürey
• FAU MoD Lecture: Disruption in science and engineering happens at scale by Prof. Dr. Johannes Brandstetter
• FAU MoD Workshop: FAU MoD Workshop (Sep. 2025) by Prof. Lorenzo Liverani | Prof. Hagen Holthusen
• FAU MoD Lecture: Exemplary applications of machine learning and optimization in quantum chemistry by Prof. Dr. Andreas Görling
• FAU MoD Lecture & workshop: AI for maths and maths for AI by Dr. François Charton
• FAU MoD Lecture: Optimization-based control for large-scale and complex systems: When and why does it work? by Prof. Dr. Lars Grüne
• FAU MoD Lecture: Mathematics of neural stem cells: Linking data and processes by Prof. Dr. Ana Martin-Villalba
• FAU MoD Lecture: FAU MoD Lecture S. Jin / N. Liu (double session) by Prof. Dr. Shi Jin and Prof. Dr. Nana Liu
• FAU MoD Lecture: Do you think you understand sex and death? Why predictions about biological processes require more than just intuition by Prof. Dr. Hanna Kokko
• FAU MoD Lecture: FAU MoD Lecture. Special December 2024 by Prof. Dr. Holger Rauhut and Prof. Dr. Christian Bär
• FAU MoD Lecture: Measuring productivity and fixedness in lexico-syntactic constructions by Prof. Dr. Stephanie Evert
• FAU MoD Lecture: New avenues for the interaction of computational mechanics and machine learning by Prof. Dr. Paolo Zunino
• FAU MoD Lecture: Discovering and Communicating Excellence by Prof. Dr. Ute Klammer
• FAU MoD Lecture: Thoughts on Machine Learning by Prof. Dr. Rupert Klein
• FAU MoD Lecture: Using system knowledge for improved sample efficiency in data-driven modeling and control of complex technical systems by Prof. Dr. Sebastian Peitz
• FAU MoD Lecture: Image Reconstruction – The Dialectic of Modelling and Learning by Prof. Dr. Martin Burger
• FAU MoD Lecture: The role of Artificial Intelligence in the future of mathematics by Prof. Dr. Amaury Hayat
• FAU MoD Lecture: FAU MoD Lecture. Special November 2023 by Prof. Dr. Michael Kohlhase and Prof. Dr. Edriss S. Titi
• FAU MoD Lecture: Free boundary regularity for the obstacle problem by Prof. Dr. Alessio Figalli
• FAU MoD Lecture: Physics-Based and Data-Driven-Based Algorithms for the Simulation of the Heart Function by Prof. Dr. Alfio Quarteroni
• FAU MoD Lecture: From Physics-Informed Machine Learning to Physics-Informed Machine Intelligence: Quo Vadimus? by Prof. Dr. George Karniadakis
• FAU MoD Lecture: From Alan Turing to contact geometry: Towards a “Fluid computer” by Prof. Dr. Eva Miranda
• FAU MoD Lecture: Applications of AAA Rational Approximation by Prof. Dr. Nick Trefethen
• FAU MoD Lecture: Learning-Based Optimization and PDE Control in User-Assignable Finite Time by Prof. Dr. Miroslav Krstic
_
Don’t miss out our last news and connect with us!

