Deep Learning in Computational Mechanics

lt;b>Stefan Kollmannsberger is an adjunct teaching professor at the Technical University of Munich (TUM) and leads the research group Simulation in Applied Mechanics at the Chair of Computational Modeling and Simulation at TUM. He graduated in Civil Engineering and spent some years as an engineer in the industry before devoting himself to Computational Mechanics in Munich. He is dedicated to teaching, science, and, of course, his family. Stefan loved to design this lecture book together with Moritz, Davide and Leon. He uses it as a basis for the introductory course in the field of Artificial Intelligence in Computational Mechanics which he teaches among other subjects at TUM.

Davide D'Angella grew up in a small Italian peninsula dividing the Venetian Lagoon from the Adriatic Sea. After his high-school graduation, being firmly convinced he did not want to study any longer, he worked a couple of years as a computer programmer. This experience made him eager to deepen his theoretical understanding of the subject, giving him the motivation to continue his studies. He headed to the University of Milan, where he obtained a bachelor's degree in computer science. After a short Au Pair experience in Germany, he moved to Munich, where he got his master's degree in Computational Science and Engineering at the Technical University of Munich. Davide is now a research associate and Ph.D. candidate at the same university in the research group Simulation in Applied Mechanics at the chair of Computational Modeling and Simulation.

As a product of the "Mauerfall", Moritz Jokeit grew up in the non-existing town of Bielefeld and the alpine foothills near Rosenheim. Following his bachelor's degree in Civil Engineering, he studied Computational Mechanics at the Technical University of Munich (TUM) and the Polytechnic University of Catalonia (UPC). His passion for deep learning and computational mechanics was transformed into a master thesis that laid the groundwork for this lecture book. After his graduation he continued his research at the Chair of Computational Modeling and Simulation. He is now a doctoral candidate at the Institute for Biomechanics at the ETH Zürich.

Introduction.- Fundamental Concepts of Machine Learning.- Neural Networks.- Machine Learning in Physics and Engineering.- Physics-informed Neural Networks.- Deep Energy Method