ECI Digital Archives

Title

Deep-learning assisted damage observations on the microscale – A new viewpoint on microstructural deformation, fracture and decohesion processes

Authors

Carl F. Kusche, RWTH Aachen, GermanyFollow
Tom Reclik, RWTH Aachen University, Aachen, Germany
Ulrich Kerzel, IUBH University of Applied Sciences, Bad Honnef, Germany
Talal Al-Samman, RWTH Aachen University, Aachen, Germany
Sandra Korte-Kerzel, RWTH Aachen University, Aachen, Germany

Conference Dates

September 29-October 4, 2019

Abstract

In recent years, state-of-the-art micromechanical systems have given researchers the ability to observe deformation processes in-situ. While this technology enables a site-specific observation, this very achievement can turn into a major limitation: To deduct conclusions about the relevance of specific processes for the bulk material, a larger field of view than typically possible in microscale observations is often required.

Please click Additional Files below to see the full abstract.

Recommended Citation

Carl F. Kusche, Tom Reclik, Ulrich Kerzel, Talal Al-Samman, and Sandra Korte-Kerzel, "Deep-learning assisted damage observations on the microscale – A new viewpoint on microstructural deformation, fracture and decohesion processes" in "Nanomechanical Testing in Materials Research and Development VII", Jon Molina-Aldareguia, IMDEA-Materials Institute, Spain Eds, ECI Symposium Series, (2019). https://dc.engconfintl.org/nanochemtest_vii/63