Damage Analysis in Dual-Phase Steel Using Deep Learning: Transfer from Uniaxial to Biaxial Straining Conditions by Image Data Augmentation

JOM, vol. 72, pp. 4420–4430

Abstract

Abstract Microstructural damage can occur during metal forming, but how and where this happens vary with the local microstructure and strain path. Large-scale analysis of such damage mechanisms is particularly important in advanced steels with a heterogeneous phase distribution. In our previous work, we demonstrated that deep learning enables a mechanism-based, statistical analysis by classifying many individual damage sites. The aim of this work is to generalize this approach to different stress states, e.g., biaxial instead of uniaxial tension, without manually labeling a large new ground-truth dataset of further micrographs and to thereby assess the changes in damage behavior with respect to stress state. Data augmentation and regularization allow us to directly apply our approach to the new, biaxial loading case. Overall, the network performance could be greatly improved and an analysis of changes in damage behavior, here the martensite crack angle distribution, with stress state can now be performed.

Authors 5

1. Setareh Medghalchi corresponding Aachen Institute for Physical Metallurgy and Materials Physics

   RWTH Aachen University

   Affiliation as printed

   Institute for Physical Metallurgy and Materials Physics, RWTH Aachen University, Aachen, Germany

2. Carl F. Kusche Aachen Institute for Physical Metallurgy and Materials Physics

   RWTH Aachen University

   Affiliation as printed

   Institute for Physical Metallurgy and Materials Physics, RWTH Aachen University, Aachen, Germany

3. Ehsan Karimi Aachen Institute for Physical Metallurgy and Materials Physics

   RWTH Aachen University

   Affiliation as printed

   Institute for Physical Metallurgy and Materials Physics, RWTH Aachen University, Aachen, Germany

4. U. Kerzel

   University of Applied Sciences Erfurt · IU International University of Applied Sciences

   Affiliation as printed

   IUBH University of Applied Science, Erfurt, Germany

5. Sandra Korte‐Kerzel Aachen Institute for Physical Metallurgy and Materials Physics

   RWTH Aachen University

   Affiliation as printed

   Institute for Physical Metallurgy and Materials Physics, RWTH Aachen University, Aachen, Germany