Artificial Intelligence in Computational Mechanics

  • Master's elective course - summer semester - 4 SWS - 6 ECTS
  • Scheduled Tuesdays 9:45 - 13:00

Objective

  • A fundamental understanding of artificial intelligence with a focus on machine learning
  • Basic implementational skills within Python and Pytorch
  • The ability to identify possible applications of artificial intelligence in the field of computational
    mechanics

Content

Introduction to Machine Learning

  • Fundamental Concepts in Machine Learning
  • Neural Networks

Machine Learning in Physics and Engineering

  • Physics-Informed Neural Networks (PINNs)
  • Deep Energy Method
  • Neural Network-based Surrogate Models
  • Inverse Problems
  • Singular Value Decomposition (SVD)
  • Reduced Order Models (ROM)
  • Sparse Identification of Nonlinear Dynamics (SINDy)

Recommended Reading

Prerequisites

Contact

Stefan KollmannsbergerLeon Herrmann