| The differences of damage initiation and accumulation of DP steels: a numerical and experimental analysis F Pütz, F Shen, M Könemann, S Münstermann International Journal of Fracture 226, 1-15, 2020 | 34 | 2020 |
| On the effect of strain and triaxiality on void evolution in a heterogeneous microstructure–A statistical and single void study of damage in DP800 steel CF Kusche, F Pütz, S Münstermann, T Al-Samman, S Korte-Kerzel Materials Science and Engineering: A 799, 140332, 2021 | 31 | 2021 |
| A novel approach to discrete representative volume element automation and generation-DRAGen M Henrich, F Pütz, S Münstermann Materials 13 (8), 1887, 2020 | 20 | 2020 |
| Generating input data for microstructure modelling: A deep learning approach using generative adversarial networks F Pütz, M Henrich, N Fehlemann, A Roth, S Münstermann Materials 13 (19), 4236, 2020 | 16 | 2020 |
| Comparative study on damage evolution during sheet metal forming of steels dp600 and dp1000 S Münstermann, J Lian, F Pütz, M Könemann, V Brinnel Journal of Physics: Conference Series 896 (1), 012074, 2017 | 12 | 2017 |
| Efficient characterization tools for deformation-induced damage at different scales CF Kusche, A Dunlap, F Pütz, C Tian, C Kirchlechner, A Aretz, A Schwedt, ... Production Engineering 14, 95-104, 2020 | 10 | 2020 |
| Reconstruction of microstructural and morphological parameters for RVE simulations with machine learning F Pütz, M Henrich, A Roth, M Könemann, S Münstermann Procedia Manufacturing 47, 629-635, 2020 | 10 | 2020 |
| Influence of synthetically generated inclusions on the stress accumulation and concentration in X65 pipeline steel N Fehlemann, Y Sparrer, F Pütz, M Konemann, S Münstermann IOP Conference Series: Materials Science and Engineering 1157 (1), 012056, 2021 | 9 | 2021 |
| Numerical quantification of damage accumulation resulting from blanking in multi-phase steel N Habibi, F Pütz, M Könemann, V Brinnel, S Münstermann, M Feistle, ... IOP Conference Series: Materials Science and Engineering 418 (1), 012058, 2018 | 8 | 2018 |
| DRAGen–A deep learning supported RVE generator framework for complex microstructure models M Henrich, N Fehlemann, F Bexter, M Neite, L Kong, F Shen, ... Heliyon 9 (8), 2023 | 4 | 2023 |
| A data driven computational microstructure analysis on the influence of martensite banding on damage in DP-steels F Pütz, N Fehlemann, V Göksu, M Henrich, M Könemann, S Münstermann Computational Materials Science 218, 111903, 2023 | 4 | 2023 |
| Identification of Martensite Bands in Dual‐Phase Steels: A Deep Learning Object Detection Approach Using Faster Region‐Based‐Convolutional Neural Network N Fehlemann, AL Suarez Aguilera, S Sandfeld, F Bexter, M Neite, D Lenz, ... steel research international 94 (7), 2200836, 2023 | 2 | 2023 |
| A simulative approach to efficient microstructure optimisation: identifying microstructural influences on the damage properties of dualphase steels F Bexter Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2023, 0 | | |
Sebastian MünstermannInstitut für Eisenhüttenkunde der RWTH AachenBestätigte E-Mail-Adresse bei iehk.rwth-aachen.de
