Physics informed neural networks for continuum micromechanics. Issue 1 (14th December 2021)

• Record Type: Journal Article
• Authors: Henkes, Alexander; Wessels, Henning; Mahnken, Rolf
• Editors: Kaliske, M.
• Is Part Of: Proceedings in applied mathematics and mechanics. Volume 21:Issue 1(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-14
• Subjects: Applied mathematics -- Periodicals; Engineering mathematics -- Periodicals; Mathematical physics -- Periodicals; 519
• DOI: 10.1002/pamm.202100040
• Languages: English
• ISSNs: 1617-7061

Abstract

Abstract: The present work proposes a Physics Informed Neural Network (PINN) for solving boundary value problems in continuum micromechanics. The presented technique is therefore an alternative to the finite element method or Fourier transform based methods. In this context, a neural network is used to approximate the function solving the partial differential equation. The theory of PINN in the context of micromechanics is developed.