| On the micromechanics of deep material networks S Gajek, M Schneider, T Böhlke Journal of the Mechanics and Physics of Solids 142, 103984, 2020 | 60 | 2020 |
| An FE–DMN method for the multiscale analysis of short fiber reinforced plastic components S Gajek, M Schneider, T Böhlke Computer Methods in Applied Mechanics and Engineering 384, 113952, 2021 | 45 | 2021 |
| An FE-DMN method for the multiscale analysis of thermomechanical composites S Gajek, M Schneider, T Böhlke Computational Mechanics 69 (5), 1087-1113, 2022 | 25 | 2022 |
| Biaxial tensile tests and microstructure-based inverse parameter identification of inhomogeneous SMC composites M Schemmann, S Gajek, T Böhlke Advances in mechanics of materials and structural analysis: In honor of …, 2018 | 17 | 2018 |
| Training deep material networks to reproduce creep loading of short fiber-reinforced thermoplastics with an inelastically-informed strategy AP Dey, F Welschinger, M Schneider, S Gajek, T Böhlke Archive of Applied Mechanics 92 (9), 2733-2755, 2022 | 12 | 2022 |
| Parameter identification by inverse modelling of biaxial tensile tests for discontinous fiber reinforced polymers M Schemmann, B Brylka, S Gajek, T Böhlke PAMM 15 (1), 355-356, 2015 | 12 | 2015 |
| Rapid inverse calibration of a multiscale model for the viscoplastic and creep behavior of short fiber-reinforced thermoplastics based on Deep Material Networks AP Dey, F Welschinger, M Schneider, S Gajek, T Böhlke International Journal of Plasticity 160, 103484, 2023 | 10 | 2023 |
| A probabilistic virtual process chain to quantify process-induced uncertainties in Sheet Molding Compounds N Meyer, S Gajek, J Görthofer, A Hrymak, L Kärger, F Henning, ... Composites Part B: Engineering 249, 110380, 2023 | 9 | 2023 |
| Efficient two‐scale simulations of microstructured materials using deep material networks S Gajek, M Schneider, T Böhlke PAMM 21 (1), e202100069, 2021 | 4 | 2021 |
| Deep material networks for efficient scale-bridging in thermomechanical simulations of solids S Gajek KIT Scientific Publishing, 2023 | 1 | 2023 |
| Material‐informed training of viscoelastic deep material networks S Gajek, M Schneider, T Böhlke PAMM 22 (1), e202200143, 2023 | | 2023 |
| Inversely identifying material parameters for a multiscale framework to model creep deformation using Deep Material Networks AP Dey, F Welschinger, M Schneider, S Gajek, T Böhlke | | |
Thomas BöhlkeInstitute of Engineering Mechanics, Chair for Continuum Mechanics, Karlsruhe Institute of Technology (KIT)Verified email at kit.edu
