7 Publications
2025 | Conference Paper | LibreCat-ID: 62079
Gröger B, Gerritzen J, Hornig A, Gude M. Modeling approaches for the decomposition behavior of preconsolidated rovings throughout local deformation processes. In: Meschut G, Bobbert M, Duflou J, et al., eds. Sheet Metal 2025. Materials Research Proceedings. Materials Research Forum LLC, Materials Research Foundations; 2025:268–275. doi:10.21741/9781644903551-33
LibreCat
| DOI
2025 | Conference Paper | LibreCat-ID: 62080
Gerritzen J, Hornig A, Gude M. Efficient failure information propagation under complex stress states in fiber reinforced polymers: From micro- to meso-scale using machine learning. In: Meschut G, Bobbert M, Duflou J, et al., eds. Sheet Metal 2025. Materials Research Proceedings. Materials Research Forum LLC, Materials Research Foundations; 2025:260–267. doi:10.21741/9781644903551-32
LibreCat
| DOI
2025 | Journal Article | LibreCat-ID: 62081
Gerritzen J, Gröger B, Zscheyge M, Hornig A, Gude M. 3D viscoelastic plastic model coupled with a continuum damage formulation for fiber reinforced polymers. Materials & Design. 2025;260. doi:10.1016/j.matdes.2025.114969
LibreCat
| DOI
2024 | Journal Article | LibreCat-ID: 62073
Gröger B, Gerritzen J, Hornig A, Gude M. Developing a numerical modelling strategy for metallic pin pressing processes in fibre reinforced thermoplastics to investigate fibre rearrangement mechanisms during joining. Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications. 2024;238(12):2286-2298. doi:10.1177/14644207241280035
LibreCat
| DOI
2024 | Conference Paper | LibreCat-ID: 62078
Gerritzen J, Hornig A, Winkler P, Gude M. Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning. In: ECCM21 - Proceedings of the 21st European Conference on Composite Materials. Vol 3. European Society for Composite Materials (ESCM); 2024:1252–1259. doi:10.60691/yj56-np80
LibreCat
| DOI
2024 | Journal Article | LibreCat-ID: 62076
Gerritzen J, Hornig A, Winkler P, Gude M. A methodology for direct parameter identification for experimental results using machine learning — Real world application to the highly non-linear deformation behavior of FRP. Computational Materials Science. 2024;244. doi:10.1016/j.commatsci.2024.113274
LibreCat
| DOI
2023 | Conference Paper | LibreCat-ID: 62082
Gröger B, Gerritzen J, Eckardt S, et al. Modelling of Composite Manufacturing Processes Incorporating Large Fibre Deformations and Process Parameter Interactions - Example Braiding. Published online 2023.
LibreCat
7 Publications
2025 | Conference Paper | LibreCat-ID: 62079
Gröger B, Gerritzen J, Hornig A, Gude M. Modeling approaches for the decomposition behavior of preconsolidated rovings throughout local deformation processes. In: Meschut G, Bobbert M, Duflou J, et al., eds. Sheet Metal 2025. Materials Research Proceedings. Materials Research Forum LLC, Materials Research Foundations; 2025:268–275. doi:10.21741/9781644903551-33
LibreCat
| DOI
2025 | Conference Paper | LibreCat-ID: 62080
Gerritzen J, Hornig A, Gude M. Efficient failure information propagation under complex stress states in fiber reinforced polymers: From micro- to meso-scale using machine learning. In: Meschut G, Bobbert M, Duflou J, et al., eds. Sheet Metal 2025. Materials Research Proceedings. Materials Research Forum LLC, Materials Research Foundations; 2025:260–267. doi:10.21741/9781644903551-32
LibreCat
| DOI
2025 | Journal Article | LibreCat-ID: 62081
Gerritzen J, Gröger B, Zscheyge M, Hornig A, Gude M. 3D viscoelastic plastic model coupled with a continuum damage formulation for fiber reinforced polymers. Materials & Design. 2025;260. doi:10.1016/j.matdes.2025.114969
LibreCat
| DOI
2024 | Journal Article | LibreCat-ID: 62073
Gröger B, Gerritzen J, Hornig A, Gude M. Developing a numerical modelling strategy for metallic pin pressing processes in fibre reinforced thermoplastics to investigate fibre rearrangement mechanisms during joining. Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications. 2024;238(12):2286-2298. doi:10.1177/14644207241280035
LibreCat
| DOI
2024 | Conference Paper | LibreCat-ID: 62078
Gerritzen J, Hornig A, Winkler P, Gude M. Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning. In: ECCM21 - Proceedings of the 21st European Conference on Composite Materials. Vol 3. European Society for Composite Materials (ESCM); 2024:1252–1259. doi:10.60691/yj56-np80
LibreCat
| DOI
2024 | Journal Article | LibreCat-ID: 62076
Gerritzen J, Hornig A, Winkler P, Gude M. A methodology for direct parameter identification for experimental results using machine learning — Real world application to the highly non-linear deformation behavior of FRP. Computational Materials Science. 2024;244. doi:10.1016/j.commatsci.2024.113274
LibreCat
| DOI
2023 | Conference Paper | LibreCat-ID: 62082
Gröger B, Gerritzen J, Eckardt S, et al. Modelling of Composite Manufacturing Processes Incorporating Large Fibre Deformations and Process Parameter Interactions - Example Braiding. Published online 2023.
LibreCat