---
_id: '65582'
abstract:
- lang: eng
text: The mechanical joining of continuous fiber-reinforced thermoplastics
(cFRTP) and metal sheets represents a promising approach for manufacturing hybrid
lightweight structures. To reduce the time and cost associated with extensive
experimental investigations, numerical modeling strategies are increasingly applied.
In this numerical study, a further step in the modelling strategy for the direct
pin-pressing (DPP) process of cFRTP and metal sheets is presented. The study focuses
on modeling and simulating the occurring deformation mechanisms of decomposition,
compaction, and separation of individual rovings on the mesoscale to analyze the
resulting material structure. For this purpose, two simplified models were derived.
The textile architecture is represented based on micrographs of cross-sections
and discretized using the finite element method. The deformation of individual
rovings during joining leads to a deformation of their initial elliptical cross
section. To capture this level of resolution, both a cohesive zone and a pure
contact approach are applied within the rovings. The highly viscous thermoplastic
melt is modeled as a fluid employing the Arbitrary Lagrange–Eulerian (ALE) method.
Matrix and roving meshes are coupled to account for fluid–structure interaction
(FSI) during process. The study shows that coupling of matrix and rovings is necessary
to obtain more accurate predictions of the deformation behaviour. Furthermore,
the cohesive zone approach is better suited to simulate the emerging deformation
mechanisms.
author:
- first_name: Benjamin
full_name: Gröger, Benjamin
last_name: Gröger
- first_name: Johannes
full_name: Gerritzen, Johannes
id: '105344'
last_name: Gerritzen
orcid: 0000-0002-0169-8602
- first_name: Andreas
full_name: Hornig, Andreas
last_name: Hornig
- first_name: Maik
full_name: Gude, Maik
last_name: Gude
citation:
ama: Gröger B, Gerritzen J, Hornig A, Gude M. Modelling Deformation Mechanisms Decomposition,
Separation and Compaction in Mechanical Joining Processes of Fiber Reinforced
Thermoplastics on Meso Scale. Key Engineering Materials. 2026;1050:227-234.
doi:10.4028/p-e8wywr
apa: Gröger, B., Gerritzen, J., Hornig, A., & Gude, M. (2026). Modelling Deformation
Mechanisms Decomposition, Separation and Compaction in Mechanical Joining Processes
of Fiber Reinforced Thermoplastics on Meso Scale. Key Engineering Materials,
1050, 227–234. https://doi.org/10.4028/p-e8wywr
bibtex: '@article{Gröger_Gerritzen_Hornig_Gude_2026, title={Modelling Deformation
Mechanisms Decomposition, Separation and Compaction in Mechanical Joining Processes
of Fiber Reinforced Thermoplastics on Meso Scale}, volume={1050}, DOI={10.4028/p-e8wywr},
journal={Key Engineering Materials}, publisher={Trans Tech Publications, Ltd.},
author={Gröger, Benjamin and Gerritzen, Johannes and Hornig, Andreas and Gude,
Maik}, year={2026}, pages={227–234} }'
chicago: 'Gröger, Benjamin, Johannes Gerritzen, Andreas Hornig, and Maik Gude. “Modelling
Deformation Mechanisms Decomposition, Separation and Compaction in Mechanical
Joining Processes of Fiber Reinforced Thermoplastics on Meso Scale.” Key Engineering
Materials 1050 (2026): 227–34. https://doi.org/10.4028/p-e8wywr.'
ieee: 'B. Gröger, J. Gerritzen, A. Hornig, and M. Gude, “Modelling Deformation Mechanisms
Decomposition, Separation and Compaction in Mechanical Joining Processes of Fiber
Reinforced Thermoplastics on Meso Scale,” Key Engineering Materials, vol.
1050, pp. 227–234, 2026, doi: 10.4028/p-e8wywr.'
mla: Gröger, Benjamin, et al. “Modelling Deformation Mechanisms Decomposition, Separation
and Compaction in Mechanical Joining Processes of Fiber Reinforced Thermoplastics
on Meso Scale.” Key Engineering Materials, vol. 1050, Trans Tech Publications,
Ltd., 2026, pp. 227–34, doi:10.4028/p-e8wywr.
short: B. Gröger, J. Gerritzen, A. Hornig, M. Gude, Key Engineering Materials 1050
(2026) 227–234.
date_created: 2026-05-07T15:07:34Z
date_updated: 2026-05-07T15:10:16Z
doi: 10.4028/p-e8wywr
intvolume: ' 1050'
language:
- iso: eng
page: 227-234
project:
- _id: '137'
name: TRR 285 - Subproject A03
- _id: '131'
name: TRR 285 - Project Area A
- _id: '130'
name: 'TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
Prozessketten'
publication: Key Engineering Materials
publication_identifier:
issn:
- 1662-9795
publication_status: published
publisher: Trans Tech Publications, Ltd.
status: public
title: Modelling Deformation Mechanisms Decomposition, Separation and Compaction in
Mechanical Joining Processes of Fiber Reinforced Thermoplastics on Meso Scale
type: journal_article
user_id: '105344'
volume: 1050
year: '2026'
...
---
_id: '62079'
abstract:
- lang: eng
text: This paper investigates two modeling approaches for the simulation of the
deformation and decomposition behavior of preconsolidated rovings above the thermoplastic
matrix{\textquoteright} melting temperature. This is crucial for capturing the
local material structure after processes introducing highly localized deformation
such as mechanical joining processes between metal and fiber reinforced thermoplastics
(FRTP). A generic finite element (FE) model is developed, incorporating interfaces
discretized through either cohesive zone (CZ) elements or Coulomb friction-based
contacts. The material parameters for the FE elements are derived from the initial
stiffness of a statistical volume element (SVE) at micro scale modelled with an
Arbitrary-Lagrange-Eulerian method for three load cases. The CZ properties calculated
are based on the shear viscosity of the composite. The CZ and contact modelling
approaches are evaluated using three load cases of the SVE, comparing force-displacement
curves. Under simple loading conditions, such as normal pressure tension and bending,
both methods produce similar results; however, in complex load cases, the CZ approach
shows clear advantages in handling interface interactions and shows robust simulations.
The CZ approach thus presents a promising method for simulating roving decomposition
in FRTP-metal joining applications above the matrix{\textquoteright} melting temperature.
author:
- first_name: Benjamin
full_name: Gröger, Benjamin
last_name: Gröger
- first_name: Johannes
full_name: Gerritzen, Johannes
id: '105344'
last_name: Gerritzen
orcid: 0000-0002-0169-8602
- first_name: Andreas
full_name: Hornig, Andreas
last_name: Hornig
- first_name: Maik
full_name: Gude, Maik
last_name: Gude
citation:
ama: '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'
apa: Gröger, B., Gerritzen, J., Hornig, A., & Gude, M. (2025). Modeling approaches
for the decomposition behavior of preconsolidated rovings throughout local deformation
processes. In G. Meschut, M. Bobbert, J. Duflou, L. Fratini, H. Hagenah, P. Martins,
M. Merklein, & F. Micari (Eds.), Sheet Metal 2025 (pp. 268–275). Materials
Research Forum LLC, Materials Research Foundations. https://doi.org/10.21741/9781644903551-33
bibtex: '@inproceedings{Gröger_Gerritzen_Hornig_Gude_2025, series={Materials Research
Proceedings}, title={Modeling approaches for the decomposition behavior of preconsolidated
rovings throughout local deformation processes}, DOI={10.21741/9781644903551-33},
booktitle={Sheet Metal 2025}, publisher={Materials Research Forum LLC, Materials
Research Foundations}, author={Gröger, Benjamin and Gerritzen, Johannes and Hornig,
Andreas and Gude, Maik}, editor={Meschut, G. and Bobbert, M. and Duflou, J. and
Fratini, L. and Hagenah, H. and Martins, P. and Merklein, M. and Micari, F.},
year={2025}, pages={268–275}, collection={Materials Research Proceedings} }'
chicago: Gröger, Benjamin, Johannes Gerritzen, Andreas Hornig, and Maik Gude. “Modeling
Approaches for the Decomposition Behavior of Preconsolidated Rovings throughout
Local Deformation Processes.” In Sheet Metal 2025, edited by G. Meschut,
M. Bobbert, J. Duflou, L. Fratini, H. Hagenah, P. Martins, M. Merklein, and F.
Micari, 268–275. Materials Research Proceedings. Materials Research Forum LLC,
Materials Research Foundations, 2025. https://doi.org/10.21741/9781644903551-33.
ieee: 'B. Gröger, J. Gerritzen, A. Hornig, and M. Gude, “Modeling approaches for
the decomposition behavior of preconsolidated rovings throughout local deformation
processes,” in Sheet Metal 2025, 2025, pp. 268–275, doi: 10.21741/9781644903551-33.'
mla: Gröger, Benjamin, et al. “Modeling Approaches for the Decomposition Behavior
of Preconsolidated Rovings throughout Local Deformation Processes.” Sheet Metal
2025, edited by G. Meschut et al., Materials Research Forum LLC, Materials
Research Foundations, 2025, pp. 268–275, doi:10.21741/9781644903551-33.
short: 'B. Gröger, 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.'
date_created: 2025-11-04T12:48:21Z
date_updated: 2026-02-27T06:43:19Z
doi: 10.21741/9781644903551-33
editor:
- first_name: G.
full_name: Meschut, G.
last_name: Meschut
- first_name: M.
full_name: Bobbert, M.
last_name: Bobbert
- first_name: J.
full_name: Duflou, J.
last_name: Duflou
- first_name: L.
full_name: Fratini, L.
last_name: Fratini
- first_name: H.
full_name: Hagenah, H.
last_name: Hagenah
- first_name: P.
full_name: Martins, P.
last_name: Martins
- first_name: M.
full_name: Merklein, M.
last_name: Merklein
- first_name: F.
full_name: Micari, F.
last_name: Micari
keyword:
- Finite Element Method (FEM)
- Process
- Thermoplastic Fiber Reinforced Plastic
language:
- iso: eng
page: 268–275
project:
- _id: '130'
name: 'TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
Prozessketten'
- _id: '137'
name: TRR 285 - Subproject A03
- _id: '131'
name: TRR 285 - Project Area A
publication: Sheet Metal 2025
publication_identifier:
isbn:
- 978-1-64490-354-4
publisher: Materials Research Forum LLC, Materials Research Foundations
series_title: Materials Research Proceedings
status: public
title: Modeling approaches for the decomposition behavior of preconsolidated rovings
throughout local deformation processes
type: conference
user_id: '105344'
year: '2025'
...
---
_id: '62080'
abstract:
- lang: eng
text: The failure behavior of fiber reinforced polymers (FRP) is strongly influenced
by their microstructure, i.e. fiber arrangement or local fiber volume content.
However, this information cannot be directly used for structural analyses, since
it requires a discretization on micrometer level. Therefore, current failure theories
do not directly account for such effects, but describe the behavior averaged over
an entire specimen. This foundation in experimentally accessible loading conditions
leads to purely theory based extension to more complex stress states without direct
validation possibilities. This work aims at leveraging micro-scale simulations
to obtain failure information under arbitrary loading conditions. The results
are propagated to the meso-scale, enabling efficient structural analyses, by means
of machine learning (ML). It is shown that the ML model is capable of correctly
assessing previously unseen stress states and therefore poses an efficient tool
of exploiting information from the micro-scale in larger simulations.
author:
- first_name: Johannes
full_name: Gerritzen, Johannes
id: '105344'
last_name: Gerritzen
orcid: 0000-0002-0169-8602
- first_name: Andreas
full_name: Hornig, Andreas
last_name: Hornig
- first_name: Maik
full_name: Gude, Maik
last_name: Gude
citation:
ama: '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'
apa: 'Gerritzen, J., Hornig, A., & Gude, M. (2025). Efficient failure information
propagation under complex stress states in fiber reinforced polymers: From micro-
to meso-scale using machine learning. In G. Meschut, M. Bobbert, J. Duflou, L.
Fratini, H. Hagenah, P. Martins, M. Merklein, & F. Micari (Eds.), Sheet
Metal 2025 (pp. 260–267). Materials Research Forum LLC, Materials Research
Foundations. https://doi.org/10.21741/9781644903551-32'
bibtex: '@inproceedings{Gerritzen_Hornig_Gude_2025, series={Materials Research Proceedings},
title={Efficient failure information propagation under complex stress states in
fiber reinforced polymers: From micro- to meso-scale using machine learning},
DOI={10.21741/9781644903551-32},
booktitle={Sheet Metal 2025}, publisher={Materials Research Forum LLC, Materials
Research Foundations}, author={Gerritzen, Johannes and Hornig, Andreas and Gude,
Maik}, editor={Meschut, G. and Bobbert, M. and Duflou, J. and Fratini, L. and
Hagenah, H. and Martins, P. and Merklein, M. and Micari, F.}, year={2025}, pages={260–267},
collection={Materials Research Proceedings} }'
chicago: 'Gerritzen, Johannes, Andreas Hornig, and Maik Gude. “Efficient Failure
Information Propagation under Complex Stress States in Fiber Reinforced Polymers:
From Micro- to Meso-Scale Using Machine Learning.” In Sheet Metal 2025,
edited by G. Meschut, M. Bobbert, J. Duflou, L. Fratini, H. Hagenah, P. Martins,
M. Merklein, and F. Micari, 260–267. Materials Research Proceedings. Materials
Research Forum LLC, Materials Research Foundations, 2025. https://doi.org/10.21741/9781644903551-32.'
ieee: 'J. Gerritzen, A. Hornig, and M. Gude, “Efficient failure information propagation
under complex stress states in fiber reinforced polymers: From micro- to meso-scale
using machine learning,” in Sheet Metal 2025, 2025, pp. 260–267, doi: 10.21741/9781644903551-32.'
mla: 'Gerritzen, Johannes, et al. “Efficient Failure Information Propagation under
Complex Stress States in Fiber Reinforced Polymers: From Micro- to Meso-Scale
Using Machine Learning.” Sheet Metal 2025, edited by G. Meschut et al.,
Materials Research Forum LLC, Materials Research Foundations, 2025, pp. 260–267,
doi:10.21741/9781644903551-32.'
short: '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.'
date_created: 2025-11-04T12:48:37Z
date_updated: 2026-02-27T06:43:37Z
doi: 10.21741/9781644903551-32
editor:
- first_name: G.
full_name: Meschut, G.
last_name: Meschut
- first_name: M.
full_name: Bobbert, M.
last_name: Bobbert
- first_name: J.
full_name: Duflou, J.
last_name: Duflou
- first_name: L.
full_name: Fratini, L.
last_name: Fratini
- first_name: H.
full_name: Hagenah, H.
last_name: Hagenah
- first_name: P.
full_name: Martins, P.
last_name: Martins
- first_name: M.
full_name: Merklein, M.
last_name: Merklein
- first_name: F.
full_name: Micari, F.
last_name: Micari
keyword:
- Failure
- Fiber Reinforced Plastic
- Machine Learning
language:
- iso: eng
page: 260–267
project:
- _id: '130'
name: 'TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
Prozessketten'
- _id: '137'
name: TRR 285 - Subproject A03
- _id: '131'
name: TRR 285 - Project Area A
publication: Sheet Metal 2025
publication_identifier:
isbn:
- 978-1-64490-354-4
publisher: Materials Research Forum LLC, Materials Research Foundations
series_title: Materials Research Proceedings
status: public
title: 'Efficient failure information propagation under complex stress states in fiber
reinforced polymers: From micro- to meso-scale using machine learning'
type: conference
user_id: '105344'
year: '2025'
...
---
_id: '62081'
article_number: '114969'
author:
- first_name: Johannes
full_name: Gerritzen, Johannes
id: '105344'
last_name: Gerritzen
orcid: 0000-0002-0169-8602
- first_name: Benjamin
full_name: Gröger, Benjamin
last_name: Gröger
- first_name: Matthias
full_name: Zscheyge, Matthias
last_name: Zscheyge
- first_name: Andreas
full_name: Hornig, Andreas
last_name: Hornig
- first_name: Maik
full_name: Gude, Maik
last_name: Gude
citation:
ama: 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
apa: Gerritzen, J., Gröger, B., Zscheyge, M., Hornig, A., & Gude, M. (2025).
3D viscoelastic plastic model coupled with a continuum damage formulation for
fiber reinforced polymers. Materials & Design, 260, Article
114969. https://doi.org/10.1016/j.matdes.2025.114969
bibtex: '@article{Gerritzen_Gröger_Zscheyge_Hornig_Gude_2025, title={3D viscoelastic
plastic model coupled with a continuum damage formulation for fiber reinforced
polymers}, volume={260}, DOI={10.1016/j.matdes.2025.114969},
number={114969}, journal={Materials & Design}, publisher={Elsevier BV},
author={Gerritzen, Johannes and Gröger, Benjamin and Zscheyge, Matthias and Hornig,
Andreas and Gude, Maik}, year={2025} }'
chicago: Gerritzen, Johannes, Benjamin Gröger, Matthias Zscheyge, Andreas Hornig,
and Maik Gude. “3D Viscoelastic Plastic Model Coupled with a Continuum Damage
Formulation for Fiber Reinforced Polymers.” Materials & Design
260 (2025). https://doi.org/10.1016/j.matdes.2025.114969.
ieee: 'J. Gerritzen, B. Gröger, M. Zscheyge, A. Hornig, and M. Gude, “3D viscoelastic
plastic model coupled with a continuum damage formulation for fiber reinforced
polymers,” Materials & Design, vol. 260, Art. no. 114969, 2025,
doi: 10.1016/j.matdes.2025.114969.'
mla: Gerritzen, Johannes, et al. “3D Viscoelastic Plastic Model Coupled with a Continuum
Damage Formulation for Fiber Reinforced Polymers.” Materials & Design,
vol. 260, 114969, Elsevier BV, 2025, doi:10.1016/j.matdes.2025.114969.
short: J. Gerritzen, B. Gröger, M. Zscheyge, A. Hornig, M. Gude, Materials &
Design 260 (2025).
date_created: 2025-11-04T12:49:13Z
date_updated: 2026-02-27T06:43:55Z
doi: 10.1016/j.matdes.2025.114969
intvolume: ' 260'
language:
- iso: eng
project:
- _id: '130'
name: 'TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
Prozessketten'
- _id: '137'
name: TRR 285 - Subproject A03
- _id: '131'
name: TRR 285 - Project Area A
publication: Materials & Design
publication_identifier:
issn:
- 0264-1275
publication_status: published
publisher: Elsevier BV
status: public
title: 3D viscoelastic plastic model coupled with a continuum damage formulation for
fiber reinforced polymers
type: journal_article
user_id: '105344'
volume: 260
year: '2025'
...
---
_id: '63828'
article_number: '100368'
author:
- first_name: Johannes
full_name: Gerritzen, Johannes
id: '105344'
last_name: Gerritzen
orcid: 0000-0002-0169-8602
- first_name: Kunal
full_name: Chopra, Kunal
last_name: Chopra
- first_name: Gregor
full_name: Reschke, Gregor
id: '98812'
last_name: Reschke
- first_name: Andreas
full_name: Hornig, Andreas
last_name: Hornig
- first_name: Alexander
full_name: Brosius, Alexander
last_name: Brosius
- first_name: Maik
full_name: Gude, Maik
last_name: Gude
citation:
ama: Gerritzen J, Chopra K, Reschke G, Hornig A, Brosius A, Gude M. Quality assurance
of clinched joints using explainable machine learning. Journal of Advanced
Joining Processes. 2025;13. doi:10.1016/j.jajp.2025.100368
apa: Gerritzen, J., Chopra, K., Reschke, G., Hornig, A., Brosius, A., & Gude,
M. (2025). Quality assurance of clinched joints using explainable machine learning.
Journal of Advanced Joining Processes, 13, Article 100368. https://doi.org/10.1016/j.jajp.2025.100368
bibtex: '@article{Gerritzen_Chopra_Reschke_Hornig_Brosius_Gude_2025, title={Quality
assurance of clinched joints using explainable machine learning}, volume={13},
DOI={10.1016/j.jajp.2025.100368},
number={100368}, journal={Journal of Advanced Joining Processes}, publisher={Elsevier
BV}, author={Gerritzen, Johannes and Chopra, Kunal and Reschke, Gregor and Hornig,
Andreas and Brosius, Alexander and Gude, Maik}, year={2025} }'
chicago: Gerritzen, Johannes, Kunal Chopra, Gregor Reschke, Andreas Hornig, Alexander
Brosius, and Maik Gude. “Quality Assurance of Clinched Joints Using Explainable
Machine Learning.” Journal of Advanced Joining Processes 13 (2025). https://doi.org/10.1016/j.jajp.2025.100368.
ieee: 'J. Gerritzen, K. Chopra, G. Reschke, A. Hornig, A. Brosius, and M. Gude,
“Quality assurance of clinched joints using explainable machine learning,” Journal
of Advanced Joining Processes, vol. 13, Art. no. 100368, 2025, doi: 10.1016/j.jajp.2025.100368.'
mla: Gerritzen, Johannes, et al. “Quality Assurance of Clinched Joints Using Explainable
Machine Learning.” Journal of Advanced Joining Processes, vol. 13, 100368,
Elsevier BV, 2025, doi:10.1016/j.jajp.2025.100368.
short: J. Gerritzen, K. Chopra, G. Reschke, A. Hornig, A. Brosius, M. Gude, Journal
of Advanced Joining Processes 13 (2025).
date_created: 2026-02-02T08:32:04Z
date_updated: 2026-02-27T06:45:47Z
doi: 10.1016/j.jajp.2025.100368
intvolume: ' 13'
language:
- iso: eng
project:
- _id: '137'
name: TRR 285 - Subproject A03
- _id: '131'
name: TRR 285 - Project Area A
- _id: '130'
name: 'TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
Prozessketten'
- _id: '133'
name: TRR 285 - Project Area C
- _id: '148'
name: TRR 285 - Subproject C04
publication: Journal of Advanced Joining Processes
publication_identifier:
issn:
- 2666-3309
publication_status: published
publisher: Elsevier BV
status: public
title: Quality assurance of clinched joints using explainable machine learning
type: journal_article
user_id: '105344'
volume: 13
year: '2025'
...
---
_id: '61149'
abstract:
- lang: eng
text: The use of continuous fiber-reinforced thermoplastics (FRTP) in automotive
industry increases due to their excellent material properties and possibility
of rapid processing. The scale spanning heterogeneity of their material structure
and its influence on the material behavior, however, presents significant challenges
for most joining technologies, such as self-piercing riveting (SPR). During mechanical
joining, the material structure is significantly altered within and around the
joining zone, heavily influencing the material behavior. A comprehensive understanding
of the underlying phenomena of material alteration during the SPR process is essential
as basis for validating numerical simulations. This study examines the material
structure at ten stages of a step-setting test of SPR with two FRTP sheets with
glass-fiber reinforcement. Utilizing X-ray computed tomography (CT), the damage
phenomena within different areas of the setting test are analyzed three-dimensionally
and key parameters are quantified. Dominating phenomena during the penetration
of the rivet into the laminate are fiber failure (FF), interfiber failure (IFF)
and fiber bending, while delamination, fiber kinking and roving splitting are
also observed. At the final stages, the bottom layers of the second sheet collapse
and form a bulge into the cavity of the die.
author:
- first_name: Alrik
full_name: Dargel, Alrik
id: '114764'
last_name: Dargel
- first_name: Benjamin
full_name: Gröger, Benjamin
last_name: Gröger
- first_name: Malte Christian
full_name: Schlichter, Malte Christian
id: '61977'
last_name: Schlichter
- first_name: Johannes
full_name: Gerritzen, Johannes
id: '105344'
last_name: Gerritzen
orcid: 0000-0002-0169-8602
- first_name: Daniel
full_name: Köhler, Daniel
id: '83408'
last_name: Köhler
- first_name: Gerson
full_name: Meschut, Gerson
id: '32056'
last_name: Meschut
orcid: 0000-0002-2763-1246
- first_name: Maik
full_name: Gude, Maik
last_name: Gude
- first_name: Robert
full_name: Kupfer, Robert
last_name: Kupfer
citation:
ama: 'Dargel A, Gröger B, Schlichter MC, et al. Local Deformation and Failure of
Composites during Self-Piercing Riveting: A CT-Based Microstructure Investigation.
In: Gomes JFS, Meguid SA, eds. Proceedings of the 8th International Conference
on Integrity-Reliability-Failure (IRF2025). FEUP; 2025. doi:10.24840/978-972-752-323-8'
apa: 'Dargel, A., Gröger, B., Schlichter, M. C., Gerritzen, J., Köhler, D., Meschut,
G., Gude, M., & Kupfer, R. (2025). Local Deformation and Failure of Composites
during Self-Piercing Riveting: A CT-Based Microstructure Investigation. In J.
F. S. Gomes & S. A. Meguid (Eds.), Proceedings of the 8th International
Conference on Integrity-Reliability-Failure (IRF2025). FEUP. https://doi.org/10.24840/978-972-752-323-8'
bibtex: '@inproceedings{Dargel_Gröger_Schlichter_Gerritzen_Köhler_Meschut_Gude_Kupfer_2025,
place={Porto}, title={Local Deformation and Failure of Composites during Self-Piercing
Riveting: A CT-Based Microstructure Investigation}, DOI={10.24840/978-972-752-323-8},
booktitle={Proceedings of the 8th International Conference on Integrity-Reliability-Failure
(IRF2025)}, publisher={FEUP}, author={Dargel, Alrik and Gröger, Benjamin and Schlichter,
Malte Christian and Gerritzen, Johannes and Köhler, Daniel and Meschut, Gerson
and Gude, Maik and Kupfer, Robert}, editor={Gomes, J.F. Silva and Meguid, Shaker
A.}, year={2025} }'
chicago: 'Dargel, Alrik, Benjamin Gröger, Malte Christian Schlichter, Johannes Gerritzen,
Daniel Köhler, Gerson Meschut, Maik Gude, and Robert Kupfer. “Local Deformation
and Failure of Composites during Self-Piercing Riveting: A CT-Based Microstructure
Investigation.” In Proceedings of the 8th International Conference on Integrity-Reliability-Failure
(IRF2025), edited by J.F. Silva Gomes and Shaker A. Meguid. Porto: FEUP, 2025.
https://doi.org/10.24840/978-972-752-323-8.'
ieee: 'A. Dargel et al., “Local Deformation and Failure of Composites during
Self-Piercing Riveting: A CT-Based Microstructure Investigation,” in Proceedings
of the 8th International Conference on Integrity-Reliability-Failure (IRF2025),
Porto, 2025, doi: 10.24840/978-972-752-323-8.'
mla: 'Dargel, Alrik, et al. “Local Deformation and Failure of Composites during
Self-Piercing Riveting: A CT-Based Microstructure Investigation.” Proceedings
of the 8th International Conference on Integrity-Reliability-Failure (IRF2025),
edited by J.F. Silva Gomes and Shaker A. Meguid, FEUP, 2025, doi:10.24840/978-972-752-323-8.'
short: 'A. Dargel, B. Gröger, M.C. Schlichter, J. Gerritzen, D. Köhler, G. Meschut,
M. Gude, R. Kupfer, in: J.F.S. Gomes, S.A. Meguid (Eds.), Proceedings of the 8th
International Conference on Integrity-Reliability-Failure (IRF2025), FEUP, Porto,
2025.'
conference:
end_date: 2025-07-18
location: Porto
name: 8th International Conference on Integrity-Reliability-Failure (IRF2025)
start_date: 2025-07-15
date_created: 2025-09-08T11:52:45Z
date_updated: 2026-05-07T08:40:51Z
doi: 10.24840/978-972-752-323-8
editor:
- first_name: J.F. Silva
full_name: Gomes, J.F. Silva
last_name: Gomes
- first_name: Shaker A.
full_name: Meguid, Shaker A.
last_name: Meguid
keyword:
- self-piercing riveting
- computed tomography
- thermoplastic composites
- process-structure-interaction
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.researchgate.net/publication/395593556_LOCAL_DEFORMATION_AND_FAILURE_OF_COMPOSITES_DURING_SELF-PIERCING_RIVETING_A_CT_BASED_MICROSTRUCTURE_INVESTIGATION
oa: '1'
place: Porto
project:
- _id: '133'
name: TRR 285 - Project Area C
- _id: '148'
name: TRR 285 - Subproject C04
- _id: '130'
name: 'TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
Prozessketten'
- _id: '131'
name: TRR 285 - Project Area A
- _id: '137'
name: TRR 285 - Subproject A03
- _id: '135'
name: TRR 285 - Subproject A01
publication: Proceedings of the 8th International Conference on Integrity-Reliability-Failure
(IRF2025)
publication_identifier:
isbn:
- '9789727523238'
publication_status: published
publisher: FEUP
status: public
title: 'Local Deformation and Failure of Composites during Self-Piercing Riveting:
A CT-Based Microstructure Investigation'
type: conference
user_id: '114764'
year: '2025'
...
---
_id: '62073'
abstract:
- lang: eng
text: A numerical modelling strategy for the direct pin pressing process
of metallic pins into continuous fibre-reinforced thermoplastic organosheets is
developed. The joining process is performed above the thermoplast’s melting temperature,
altering the initial material structure of the composite by fibre rearrangement,
which in turn influences the load-bearing capacity of the joint. Therefore, the
modelling strategy aims at predicting the resultant material structure after pin
pressing. The modelling approach considers both the textile architecture and the
process parameters (temperature, tool velocity). A sub-meso modelling framework
for the fibres based on a multi-filament approach is used. The interaction between
fibres and the thermoplastic melt, as well as the matrix flow, is modelled using
the Arbitrary Lagrangian Eulerian method. This allows for the prediction of matrix-rich
zones and fibre rearrangement around the pin. The promising results show a good
agreement of the resultant material structure in terms of compaction and fibre
volume content around the pressed pin. Characteristic parameters show an underestimation
of the laminate thickness below the pin. Moreover, an evaluation method for evaluating
the orientation changes of the virtual multi-filaments is developed and presented
to observe and assess fibre rearrangement and fibre volume content in detail during
the numerical process simulation. It can be seen that only fibres around the pin
are displaced and not in the whole molten area. Furthermore, it can be observed
in detail that the initial position of the fibres in relation to the pin determines
whether the fibres are displaced in the in-plane or out-of-plane direction.
author:
- first_name: B.
full_name: Gröger, B.
last_name: Gröger
- first_name: Johannes
full_name: Gerritzen, Johannes
id: '105344'
last_name: Gerritzen
orcid: 0000-0002-0169-8602
- first_name: A.
full_name: Hornig, A.
last_name: Hornig
- first_name: M.
full_name: Gude, M.
last_name: Gude
citation:
ama: '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'
apa: 'Gröger, B., Gerritzen, J., Hornig, A., & Gude, M. (2024). 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, 238(12), 2286–2298. https://doi.org/10.1177/14644207241280035'
bibtex: '@article{Gröger_Gerritzen_Hornig_Gude_2024, title={Developing a numerical
modelling strategy for metallic pin pressing processes in fibre reinforced thermoplastics
to investigate fibre rearrangement mechanisms during joining}, volume={238}, DOI={10.1177/14644207241280035},
number={12}, journal={Proceedings of the Institution of Mechanical Engineers,
Part L: Journal of Materials: Design and Applications}, publisher={SAGE Publications},
author={Gröger, B. and Gerritzen, Johannes and Hornig, A. and Gude, M.}, year={2024},
pages={2286–2298} }'
chicago: 'Gröger, B., Johannes Gerritzen, A. Hornig, and M. Gude. “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 238, no. 12 (2024): 2286–98. https://doi.org/10.1177/14644207241280035.'
ieee: 'B. Gröger, J. Gerritzen, A. Hornig, and M. Gude, “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, vol. 238, no. 12, pp. 2286–2298, 2024, doi: 10.1177/14644207241280035.'
mla: 'Gröger, B., et al. “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,
vol. 238, no. 12, SAGE Publications, 2024, pp. 2286–98, doi:10.1177/14644207241280035.'
short: 'B. Gröger, 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.'
date_created: 2025-11-04T12:34:11Z
date_updated: 2026-02-27T06:45:59Z
doi: 10.1177/14644207241280035
intvolume: ' 238'
issue: '12'
language:
- iso: eng
page: 2286-2298
project:
- _id: '130'
name: 'TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
Prozessketten'
- _id: '137'
name: TRR 285 - Subproject A03
- _id: '131'
name: TRR 285 - Project Area A
publication: 'Proceedings of the Institution of Mechanical Engineers, Part L: Journal
of Materials: Design and Applications'
publication_identifier:
issn:
- 1464-4207
- 2041-3076
publication_status: published
publisher: SAGE Publications
status: public
title: Developing a numerical modelling strategy for metallic pin pressing processes
in fibre reinforced thermoplastics to investigate fibre rearrangement mechanisms
during joining
type: journal_article
user_id: '105344'
volume: 238
year: '2024'
...
---
_id: '62078'
abstract:
- lang: eng
text: 'Fiber reinforced plastics (FRP) exhibit strongly non-linear deformation behavior.
To capture this in simulations, intricate models with a variety of parameters
are typically used. The identification of values for such parameters is highly
challenging and requires in depth understanding of the model itself. Machine learning
(ML) is a promising approach for alleviating this challenge by directly predicting
parameters based on experimental results. So far, this works mostly for purely
artificial data. In this work, two approaches to generalize to experimental data
are investigated: a sequential approach, leveraging understanding of the constitutive
model and a direct, purely data driven approach. This is exemplary carried out
for a highly non-linear strain rate dependent constitutive model for the shear
behavior of FRP.The sequential model is found to work better on both artificial
and experimental data. It is capable of extracting well suited parameters from
the artificial data under realistic conditions. For the experimental data, the
model performance depends on the composition of the experimental curves, varying
between excellently suiting and reasonable predictions. Taking the expert knowledge
into account for ML-model training led to far better results than the purely data
driven approach. Robustifying the model predictions on experimental data promises
further improvement. '
author:
- first_name: Johannes
full_name: Gerritzen, Johannes
id: '105344'
last_name: Gerritzen
orcid: 0000-0002-0169-8602
- first_name: Andreas
full_name: Hornig, Andreas
last_name: Hornig
- first_name: Peter
full_name: Winkler, Peter
last_name: Winkler
- first_name: Maik
full_name: Gude, Maik
last_name: Gude
citation:
ama: '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'
apa: Gerritzen, J., Hornig, A., Winkler, P., & Gude, M. (2024). Direct parameter
identification for highly nonlinear strain rate dependent constitutive models
using machine learning. ECCM21 - Proceedings of the 21st European Conference
on Composite Materials, 3, 1252–1259. https://doi.org/10.60691/yj56-np80
bibtex: '@inproceedings{Gerritzen_Hornig_Winkler_Gude_2024, title={Direct parameter
identification for highly nonlinear strain rate dependent constitutive models
using machine learning}, volume={3}, DOI={10.60691/yj56-np80},
booktitle={ECCM21 - Proceedings of the 21st European Conference on Composite Materials},
publisher={European Society for Composite Materials (ESCM)}, author={Gerritzen,
Johannes and Hornig, Andreas and Winkler, Peter and Gude, Maik}, year={2024},
pages={1252–1259} }'
chicago: Gerritzen, Johannes, Andreas Hornig, Peter Winkler, and Maik Gude. “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, 3:1252–1259. European Society for Composite
Materials (ESCM), 2024. https://doi.org/10.60691/yj56-np80.
ieee: 'J. Gerritzen, A. Hornig, P. Winkler, and M. Gude, “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,
2024, vol. 3, pp. 1252–1259, doi: 10.60691/yj56-np80.'
mla: Gerritzen, Johannes, et al. “Direct Parameter Identification for Highly Nonlinear
Strain Rate Dependent Constitutive Models Using Machine Learning.” ECCM21 -
Proceedings of the 21st European Conference on Composite Materials, vol. 3,
European Society for Composite Materials (ESCM), 2024, pp. 1252–1259, doi:10.60691/yj56-np80.
short: '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.'
date_created: 2025-11-04T12:47:06Z
date_updated: 2026-02-27T06:46:21Z
doi: 10.60691/yj56-np80
intvolume: ' 3'
keyword:
- Direct parameter identification
- Machine learning
- Convolutional neural networks
- Strain rate dependency
- Fiber reinforced plastics
- woven composites
- segmentation
- synthetic training data
- x-ray computed tomography
language:
- iso: eng
page: 1252–1259
project:
- _id: '130'
name: 'TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
Prozessketten'
- _id: '137'
name: TRR 285 - Subproject A03
- _id: '131'
name: TRR 285 - Project Area A
publication: ECCM21 - Proceedings of the 21st European Conference on Composite Materials
publication_identifier:
isbn:
- 978-2-912985-01-9
publisher: European Society for Composite Materials (ESCM)
status: public
title: Direct parameter identification for highly nonlinear strain rate dependent
constitutive models using machine learning
type: conference
user_id: '105344'
volume: 3
year: '2024'
...
---
_id: '62076'
article_number: '113274'
author:
- first_name: Johannes
full_name: Gerritzen, Johannes
id: '105344'
last_name: Gerritzen
orcid: 0000-0002-0169-8602
- first_name: Andreas
full_name: Hornig, Andreas
last_name: Hornig
- first_name: Peter
full_name: Winkler, Peter
last_name: Winkler
- first_name: Maik
full_name: Gude, Maik
last_name: Gude
citation:
ama: 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
apa: Gerritzen, J., Hornig, A., Winkler, P., & Gude, M. (2024). 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, 244, Article 113274. https://doi.org/10.1016/j.commatsci.2024.113274
bibtex: '@article{Gerritzen_Hornig_Winkler_Gude_2024, title={A methodology for direct
parameter identification for experimental results using machine learning — Real
world application to the highly non-linear deformation behavior of FRP}, volume={244},
DOI={10.1016/j.commatsci.2024.113274},
number={113274}, journal={Computational Materials Science}, publisher={Elsevier
BV}, author={Gerritzen, Johannes and Hornig, Andreas and Winkler, Peter and Gude,
Maik}, year={2024} }'
chicago: Gerritzen, Johannes, Andreas Hornig, Peter Winkler, and Maik Gude. “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 244 (2024). https://doi.org/10.1016/j.commatsci.2024.113274.
ieee: 'J. Gerritzen, A. Hornig, P. Winkler, and M. Gude, “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, vol. 244, Art. no. 113274, 2024, doi: 10.1016/j.commatsci.2024.113274.'
mla: Gerritzen, Johannes, et al. “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,
vol. 244, 113274, Elsevier BV, 2024, doi:10.1016/j.commatsci.2024.113274.
short: J. Gerritzen, A. Hornig, P. Winkler, M. Gude, Computational Materials Science
244 (2024).
date_created: 2025-11-04T12:37:42Z
date_updated: 2026-02-27T06:46:35Z
doi: 10.1016/j.commatsci.2024.113274
intvolume: ' 244'
language:
- iso: eng
project:
- _id: '130'
name: 'TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
Prozessketten'
- _id: '137'
name: TRR 285 - Subproject A03
- _id: '131'
name: TRR 285 - Project Area A
publication: Computational Materials Science
publication_identifier:
issn:
- 0927-0256
publication_status: published
publisher: Elsevier BV
status: public
title: A methodology for direct parameter identification for experimental results
using machine learning — Real world application to the highly non-linear deformation
behavior of FRP
type: journal_article
user_id: '105344'
volume: 244
year: '2024'
...
---
_id: '62082'
author:
- first_name: Benjamin
full_name: Gröger, Benjamin
last_name: Gröger
- first_name: Johannes
full_name: Gerritzen, Johannes
id: '105344'
last_name: Gerritzen
orcid: 0000-0002-0169-8602
- first_name: Simon
full_name: Eckardt, Simon
last_name: Eckardt
- first_name: Anton
full_name: Gelencsér, Anton
last_name: Gelencsér
- first_name: Eckart
full_name: Kunze, Eckart
last_name: Kunze
- first_name: Andreas
full_name: Hornig, Andreas
last_name: Hornig
- first_name: Richard
full_name: Protz, Richard
last_name: Protz
- first_name: Maik
full_name: Gude, Maik
last_name: Gude
citation:
ama: 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.
apa: Gröger, B., Gerritzen, J., Eckardt, S., Gelencsér, A., Kunze, E., Hornig, A.,
Protz, R., & Gude, M. (2023). Modelling of Composite Manufacturing Processes
Incorporating Large Fibre Deformations and Process Parameter Interactions - Example
Braiding. Twenty-Third International Conference on Composite Materials (ICCM23),
Belfast.
bibtex: '@article{Gröger_Gerritzen_Eckardt_Gelencsér_Kunze_Hornig_Protz_Gude_2023,
series={Proceedings of the 2023 International Conference on Composite Materials
(ICCM23)}, title={Modelling of Composite Manufacturing Processes Incorporating
Large Fibre Deformations and Process Parameter Interactions - Example Braiding},
author={Gröger, Benjamin and Gerritzen, Johannes and Eckardt, Simon and Gelencsér,
Anton and Kunze, Eckart and Hornig, Andreas and Protz, Richard and Gude, Maik},
year={2023}, collection={Proceedings of the 2023 International Conference on Composite
Materials (ICCM23)} }'
chicago: Gröger, Benjamin, Johannes Gerritzen, Simon Eckardt, Anton Gelencsér, Eckart
Kunze, Andreas Hornig, Richard Protz, and Maik Gude. “Modelling of Composite Manufacturing
Processes Incorporating Large Fibre Deformations and Process Parameter Interactions
- Example Braiding.” Proceedings of the 2023 International Conference on Composite
Materials (ICCM23), 2023.
ieee: B. Gröger et al., “Modelling of Composite Manufacturing Processes Incorporating
Large Fibre Deformations and Process Parameter Interactions - Example Braiding.”
2023.
mla: Gröger, Benjamin, et al. Modelling of Composite Manufacturing Processes
Incorporating Large Fibre Deformations and Process Parameter Interactions - Example
Braiding. 2023.
short: B. Gröger, J. Gerritzen, S. Eckardt, A. Gelencsér, E. Kunze, A. Hornig, R.
Protz, M. Gude, (2023).
conference:
end_date: 2023-08-06
location: Belfast
name: Twenty-Third International Conference on Composite Materials (ICCM23)
start_date: 2023-08-01
date_created: 2025-11-04T14:59:47Z
date_updated: 2026-02-27T06:46:51Z
language:
- iso: eng
project:
- _id: '130'
name: 'TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
Prozessketten'
- _id: '137'
name: TRR 285 - Subproject A03
- _id: '131'
name: TRR 285 - Project Area A
series_title: Proceedings of the 2023 International Conference on Composite Materials
(ICCM23)
status: public
title: Modelling of Composite Manufacturing Processes Incorporating Large Fibre Deformations
and Process Parameter Interactions - Example Braiding
type: conference
user_id: '105344'
year: '2023'
...
---
_id: '63829'
abstract:
- lang: eng
text: 'The 3D shear deformation and failure behaviour of a glass fibre reinforced
polypropylene in a shear strain rate range of γ˙=2.2×10−4 to 3.4 1s is investigated.
An Iosipescu testing setup on a servo-hydraulic high speed testing unit is used
to experimentally characterise the in-plane and out-of-plane behaviour utilising
three specimen configurations (12-, 13- and 31-direction). The experimental procedure
as well as the testing results are presented and discussed. The measured shear
stress–shear strain relations indicate a highly nonlinear behaviour and a distinct
rate dependency. Two methods are investigated to derive according material characteristics:
a classical engineering approach based on moduli and strengths and a data driven
approach based on the curve progression. In all cases a Johnson–Cook based formulation
is used to describe rate dependency. The analysis methodologies as well as the
derived model parameters are described and discussed in detail. It is shown that
a phenomenologically enhanced regression can be used to obtain material characteristics
for a generalising constitutive model based on the data driven approach.'
article_number: '318'
article_type: original
author:
- first_name: Johannes
full_name: Gerritzen, Johannes
id: '105344'
last_name: Gerritzen
orcid: 0000-0002-0169-8602
- first_name: Andreas
full_name: Hornig, Andreas
last_name: Hornig
- first_name: Benjamin
full_name: Gröger, Benjamin
last_name: Gröger
- first_name: Maik
full_name: Gude, Maik
last_name: Gude
citation:
ama: 'Gerritzen J, Hornig A, Gröger B, Gude M. A Data Driven Modelling Approach
for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic
Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling
Parameters. Journal of Composites Science. 2022;6(10). doi:10.3390/jcs6100318'
apa: 'Gerritzen, J., Hornig, A., Gröger, B., & Gude, M. (2022). A Data Driven
Modelling Approach for the Strain Rate Dependent 3D Shear Deformation and Failure
of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation and
Deriving Modelling Parameters. Journal of Composites Science, 6(10),
Article 318. https://doi.org/10.3390/jcs6100318'
bibtex: '@article{Gerritzen_Hornig_Gröger_Gude_2022, title={A Data Driven Modelling
Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic
Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling
Parameters}, volume={6}, DOI={10.3390/jcs6100318},
number={10318}, journal={Journal of Composites Science}, publisher={MDPI AG},
author={Gerritzen, Johannes and Hornig, Andreas and Gröger, Benjamin and Gude,
Maik}, year={2022} }'
chicago: 'Gerritzen, Johannes, Andreas Hornig, Benjamin Gröger, and Maik Gude. “A
Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation
and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation
and Deriving Modelling Parameters.” Journal of Composites Science 6, no.
10 (2022). https://doi.org/10.3390/jcs6100318.'
ieee: 'J. Gerritzen, A. Hornig, B. Gröger, and M. Gude, “A Data Driven Modelling
Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic
Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling
Parameters,” Journal of Composites Science, vol. 6, no. 10, Art. no. 318,
2022, doi: 10.3390/jcs6100318.'
mla: 'Gerritzen, Johannes, et al. “A Data Driven Modelling Approach for the Strain
Rate Dependent 3D Shear Deformation and Failure of Thermoplastic Fibre Reinforced
Composites: Experimental Characterisation and Deriving Modelling Parameters.”
Journal of Composites Science, vol. 6, no. 10, 318, MDPI AG, 2022, doi:10.3390/jcs6100318.'
short: J. Gerritzen, A. Hornig, B. Gröger, M. Gude, Journal of Composites Science
6 (2022).
date_created: 2026-02-02T08:41:00Z
date_updated: 2026-02-27T06:47:18Z
doi: 10.3390/jcs6100318
intvolume: ' 6'
issue: '10'
language:
- iso: eng
project:
- _id: '137'
name: TRR 285 - Subproject A03
- _id: '131'
name: TRR 285 - Project Area A
- _id: '130'
name: 'TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
Prozessketten'
publication: Journal of Composites Science
publication_identifier:
issn:
- 2504-477X
publication_status: published
publisher: MDPI AG
status: public
title: 'A Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation
and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation
and Deriving Modelling Parameters'
type: journal_article
user_id: '105344'
volume: 6
year: '2022'
...