TRR 285 - Subproject A03
?berblick
Key Facts
- Art des Projektes:
- Sonstiger Zweck
- Laufzeit:
- 01/2019 - 06/2027
Detailinformationen
Publikationen
Modeling approaches for the decomposition behavior of preconsolidated rovings throughout local deformation processes
B. Gr?ger, J. Gerritzen, A. Hornig, M. Gude, in: G. Meschut, M. Bobbert, J. Duflou, L. Fratini, H. Hagenah, P. Martins, M. Merklein, F. Micari (Eds.), Sheet Metal 2025, Materials Research Forum LLC, Materials Research Foundations, 2025, pp. 268–275.
Efficient failure information propagation under complex stress states in fiber reinforced polymers: From micro- to meso-scale using machine learning
J. Gerritzen, A. Hornig, M. Gude, in: G. Meschut, M. Bobbert, J. Duflou, L. Fratini, H. Hagenah, P. Martins, M. Merklein, F. Micari (Eds.), Sheet Metal 2025, Materials Research Forum LLC, Materials Research Foundations, 2025, pp. 260–267.
3D viscoelastic plastic model coupled with a continuum damage formulation for fiber reinforced polymers
J. Gerritzen, B. Gr?ger, M. Zscheyge, A. Hornig, M. Gude, Materials & Design 260 (2025).
Developing a numerical modelling strategy for metallic pin pressing processes in fibre reinforced thermoplastics to investigate fibre rearrangement mechanisms during joining
B. Gr?ger, J. Gerritzen, A. Hornig, M. Gude, Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications 238 (2024) 2286–2298.
Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning
Alle Publikationen anzeigen
J. Gerritzen, A. Hornig, P. Winkler, M. Gude, in: ECCM21 - Proceedings of the 21st European Conference on Composite Materials, European Society for Composite Materials (ESCM), 2024, pp. 1252–1259.