An approach to encode divergence-free stress fields in neural approximations based on stress potentials
Computer Methods in Applied Mechanics and Engineering, vol. 463, pp. 119403
Authors 8
-
Max-Planck-Institut für Nachhaltige Materialien
Affiliation as printed
Circular Metallurgy and Alloy Design, Max–Planck Institute for Sustainable Materials, Düsseldorf, Germany
-
Max Planck Institute for Dynamics of Complex Technical Systems
Affiliation as printed
Computational Methods in Systems and Control Theory, Max–Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
-
Max-Planck-Institut für Nachhaltige Materialien
Affiliation as printed
Circular Metallurgy and Alloy Design, Max–Planck Institute for Sustainable Materials, Düsseldorf, Germany
-
David Oexle corresponding
Max Planck Institute for Dynamics of Complex Technical Systems
Affiliation as printed
Computational Methods in Systems and Control Theory, Max–Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
-
Max-Planck-Institut für Nachhaltige Materialien
Affiliation as printed
Circular Metallurgy and Alloy Design, Max–Planck Institute for Sustainable Materials, Düsseldorf, Germany
-
Max-Planck-Institut für Nachhaltige Materialien · RWTH Aachen University
Affiliation as printed
Circular Metallurgy and Alloy Design, Max–Planck Institute for Sustainable Materials, Düsseldorf, Germany
Material Mechanics, RWTH Aachen University, Aachen, Germany
-
Max Planck Institute for Dynamics of Complex Technical Systems
Affiliation as printed
Computational Methods in Systems and Control Theory, Max–Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
-
Max-Planck-Institut für Nachhaltige Materialien
Affiliation as printed
Circular Metallurgy and Alloy Design, Max–Planck Institute for Sustainable Materials, Düsseldorf, Germany
Cited by 0 stored of 0
No patents citing this paper on Lens.org (checked 2026-10-06).