---
_id: '58491'
abstract:
- lang: eng
text: Similar to bulk metal forming, clinch joining is characterised by
large plastic deformations and a variety of different 3D stress states, including
severe compression. However, inherent to plastic forming is the nucleation and
growth of defects, whose detrimental effects on the material behaviour can be
described by continuum damage models and eventually lead to material failure.
As the damage evolution strongly depends on the stress state, a stress-state-dependent
model is utilised to correctly track the accumulation. To formulate and parameterise
this model, besides classical experiments, so-called modified punch tests are
also integrated herein to enhance the calibration of the failure model by capturing
a larger range of stress states and metal-forming-specific loading conditions.
Moreover, when highly ductile materials are considered, such as the dual-phase
steel HCT590X and the aluminium alloy EN AW-6014 T4 investigated here, strong
necking and localisation might occur prior to fracture. This can alter the stress
state and affect the actual strain at failure. This influence is captured by coupling
plasticity and damage to incorporate the damage-induced softening effect. Its
relative importance is shown by conducting inverse parameter identifications to
determine damage and failure parameters for both mentioned ductile metals based
on up to 12 different experiments.
article_number: '157'
author:
- first_name: Johannes
full_name: Friedlein, Johannes
last_name: Friedlein
- first_name: Max
full_name: Böhnke, Max
last_name: Böhnke
- first_name: Malte
full_name: Schlichter, Malte
last_name: Schlichter
- first_name: Mathias
full_name: Bobbert, Mathias
last_name: Bobbert
- first_name: Gerson
full_name: Meschut, Gerson
last_name: Meschut
- first_name: Julia
full_name: Mergheim, Julia
last_name: Mergheim
- first_name: Paul
full_name: Steinmann, Paul
last_name: Steinmann
citation:
ama: Friedlein J, Böhnke M, Schlichter M, et al. Material Parameter Identification
for a Stress-State-Dependent Ductile Damage and Failure Model Applied to Clinch
Joining. Journal of Manufacturing and Materials Processing. 2024;8(4).
doi:10.3390/jmmp8040157
apa: Friedlein, J., Böhnke, M., Schlichter, M., Bobbert, M., Meschut, G., Mergheim,
J., & Steinmann, P. (2024). Material Parameter Identification for a Stress-State-Dependent
Ductile Damage and Failure Model Applied to Clinch Joining. Journal of Manufacturing
and Materials Processing, 8(4), Article 157. https://doi.org/10.3390/jmmp8040157
bibtex: '@article{Friedlein_Böhnke_Schlichter_Bobbert_Meschut_Mergheim_Steinmann_2024,
title={Material Parameter Identification for a Stress-State-Dependent Ductile
Damage and Failure Model Applied to Clinch Joining}, volume={8}, DOI={10.3390/jmmp8040157},
number={4157}, journal={Journal of Manufacturing and Materials Processing}, publisher={MDPI
AG}, author={Friedlein, Johannes and Böhnke, Max and Schlichter, Malte and Bobbert,
Mathias and Meschut, Gerson and Mergheim, Julia and Steinmann, Paul}, year={2024}
}'
chicago: Friedlein, Johannes, Max Böhnke, Malte Schlichter, Mathias Bobbert, Gerson
Meschut, Julia Mergheim, and Paul Steinmann. “Material Parameter Identification
for a Stress-State-Dependent Ductile Damage and Failure Model Applied to Clinch
Joining.” Journal of Manufacturing and Materials Processing 8, no. 4 (2024).
https://doi.org/10.3390/jmmp8040157.
ieee: 'J. Friedlein et al., “Material Parameter Identification for a Stress-State-Dependent
Ductile Damage and Failure Model Applied to Clinch Joining,” Journal of Manufacturing
and Materials Processing, vol. 8, no. 4, Art. no. 157, 2024, doi: 10.3390/jmmp8040157.'
mla: Friedlein, Johannes, et al. “Material Parameter Identification for a Stress-State-Dependent
Ductile Damage and Failure Model Applied to Clinch Joining.” Journal of Manufacturing
and Materials Processing, vol. 8, no. 4, 157, MDPI AG, 2024, doi:10.3390/jmmp8040157.
short: J. Friedlein, M. Böhnke, M. Schlichter, M. Bobbert, G. Meschut, J. Mergheim,
P. Steinmann, Journal of Manufacturing and Materials Processing 8 (2024).
date_created: 2025-01-31T16:59:13Z
date_updated: 2025-01-31T17:03:34Z
doi: 10.3390/jmmp8040157
intvolume: ' 8'
issue: '4'
keyword:
- ductile damage
- stress-state dependency
- failure
- parameter identification
- punch test
- clinching
language:
- iso: eng
project:
- _id: '130'
grant_number: '418701707'
name: 'TRR 285: TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen
Prozessketten'
- _id: '131'
name: 'TRR 285 - A: TRR 285 - Project Area A'
- _id: '139'
name: 'TRR 285 – A05: TRR 285 - Subproject A05'
publication: Journal of Manufacturing and Materials Processing
publication_identifier:
issn:
- 2504-4494
publication_status: published
publisher: MDPI AG
status: public
title: Material Parameter Identification for a Stress-State-Dependent Ductile Damage
and Failure Model Applied to Clinch Joining
type: journal_article
user_id: '84990'
volume: 8
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: '34211'
abstract:
- lang: eng
text: "Nowadays, clinching is a widely used joining technique, where sheets are
joined by pure deformation to create an interlock without the need for auxiliary
parts. This leads to advantages such as reduced joining time and manufacturing\r\ncosts.
On the other hand, the joint strength solely relies on directed material deformation,
which renders an accurate material modelling essential to reliably predict the
joint forming. The formation of the joint locally involves large plastic strains
and possibly complex non-proportional loading paths, as typical of many metal
forming applications. Consequently, a finite plasticity formulation is utilised
incorporating a Chaboche–Rousselier kinematic hardening law to capture the Bauschinger
effect. Material parameters are identified from tension–compression tests on miniature
spec-\r\nimens for the dual-phase steel HCT590X. The resulting material model
is implemented in LS-Dyna to study the locally diverse loading paths and give
a quantitative statement on the importance of kinematic hardening for clinching.
It turns out that the Bauschinger effect mainly affects the springback of the
sheets and has a smaller effect on the joint forming itself."
author:
- first_name: Johannes
full_name: Friedlein, Johannes
last_name: Friedlein
- first_name: Julia
full_name: Mergheim, Julia
last_name: Mergheim
- first_name: Paul
full_name: Steinmann, Paul
last_name: Steinmann
citation:
ama: 'Friedlein J, Mergheim J, Steinmann P. Influence of Kinematic Hardening on
Clinch Joining of Dual-Phase Steel HCT590X Sheet Metal. In: The Minerals, Metals
& Materials Series. Springer International Publishing; 2022. doi:10.1007/978-3-031-06212-4_31'
apa: Friedlein, J., Mergheim, J., & Steinmann, P. (2022). Influence of Kinematic
Hardening on Clinch Joining of Dual-Phase Steel HCT590X Sheet Metal. In The
Minerals, Metals & Materials Series. Springer International Publishing.
https://doi.org/10.1007/978-3-031-06212-4_31
bibtex: '@inbook{Friedlein_Mergheim_Steinmann_2022, place={Cham}, title={Influence
of Kinematic Hardening on Clinch Joining of Dual-Phase Steel HCT590X Sheet Metal},
DOI={10.1007/978-3-031-06212-4_31},
booktitle={The Minerals, Metals & Materials Series}, publisher={Springer
International Publishing}, author={Friedlein, Johannes and Mergheim, Julia and
Steinmann, Paul}, year={2022} }'
chicago: 'Friedlein, Johannes, Julia Mergheim, and Paul Steinmann. “Influence of
Kinematic Hardening on Clinch Joining of Dual-Phase Steel HCT590X Sheet Metal.”
In The Minerals, Metals & Materials Series. Cham: Springer International
Publishing, 2022. https://doi.org/10.1007/978-3-031-06212-4_31.'
ieee: 'J. Friedlein, J. Mergheim, and P. Steinmann, “Influence of Kinematic Hardening
on Clinch Joining of Dual-Phase Steel HCT590X Sheet Metal,” in The Minerals,
Metals & Materials Series, Cham: Springer International Publishing,
2022.'
mla: Friedlein, Johannes, et al. “Influence of Kinematic Hardening on Clinch Joining
of Dual-Phase Steel HCT590X Sheet Metal.” The Minerals, Metals & Materials
Series, Springer International Publishing, 2022, doi:10.1007/978-3-031-06212-4_31.
short: 'J. Friedlein, J. Mergheim, P. Steinmann, in: The Minerals, Metals &
Materials Series, Springer International Publishing, Cham, 2022.'
date_created: 2022-12-05T21:01:29Z
date_updated: 2022-12-05T21:05:52Z
doi: 10.1007/978-3-031-06212-4_31
keyword:
- Clinching
- Material modelling
- Kinematic hardening
- Parameter identification
- Bauschinger effect
language:
- iso: eng
place: Cham
project:
- _id: '130'
grant_number: '418701707'
name: 'TRR 285: TRR 285'
- _id: '131'
name: 'TRR 285 - A: TRR 285 - Project Area A'
- _id: '139'
name: 'TRR 285 – A05: TRR 285 - Subproject A05'
publication: The Minerals, Metals & Materials Series
publication_identifier:
isbn:
- '9783031062117'
- '9783031062124'
issn:
- 2367-1181
- 2367-1696
publication_status: published
publisher: Springer International Publishing
status: public
title: Influence of Kinematic Hardening on Clinch Joining of Dual-Phase Steel HCT590X
Sheet Metal
type: book_chapter
user_id: '7850'
year: '2022'
...
---
_id: '9992'
abstract:
- lang: eng
text: State-of-the-art industrial compact high power electronic packages require
copper-copper interconnections with larger cross sections made by ultrasonic bonding.
In comparison to aluminium-copper, copper-copper interconnections require increased
normal forces and ultrasonic power, which might lead to substrate damage due to
increased mechanical stresses. One option to raise friction energy without increasing
vibration amplitude between wire and substrate or bonding force is the use of
two-dimensional vibration. The first part of this contribution reports on the
development of a novel bonding system that executes two-dimensional vibrations
of a tool-tip to bond a nail- like pin onto a copper substrate. Since intermetallic
bonds only form properly when surfaces are clean, oxide free and activated, the
geometries of tool-tip and pin were optimised using finite element analysis. To
maximize the area of the bonded annulus the distribution of normal pressure was
optimized by varying the convexity of the bottom side of the pin. Second, a statistical
model obtained from an experimental parameter study shows the influence of different
bonding parameters on the bond result. To find bonding parameters with the minimum
number of tests, the experiments have been planned using a D-optimal experimental
design approach.
author:
- first_name: Collin
full_name: Dymel, Collin
id: '66833'
last_name: Dymel
- first_name: Paul
full_name: Eichwald, Paul
last_name: Eichwald
- first_name: Reinhard
full_name: Schemmel, Reinhard
id: '28647'
last_name: Schemmel
- first_name: Tobias
full_name: Hemsel, Tobias
id: '210'
last_name: Hemsel
- first_name: Michael
full_name: Brökelmann, Michael
last_name: Brökelmann
- first_name: Matthias
full_name: Hunstig, Matthias
last_name: Hunstig
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Dymel C, Eichwald P, Schemmel R, et al. Numerical and statistical investigation
of weld formation in a novel two-dimensional copper-copper bonding process. In:
(Proceedings of 7th Electronics System-Integration Technology Conference, Dresden,
Germany). ; 2018:1-6.'
apa: Dymel, C., Eichwald, P., Schemmel, R., Hemsel, T., Brökelmann, M., Hunstig,
M., & Sextro, W. (2018). Numerical and statistical investigation of weld formation
in a novel two-dimensional copper-copper bonding process. In (Proceedings of
7th Electronics System-Integration Technology Conference, Dresden, Germany)
(pp. 1–6).
bibtex: '@inproceedings{Dymel_Eichwald_Schemmel_Hemsel_Brökelmann_Hunstig_Sextro_2018,
title={Numerical and statistical investigation of weld formation in a novel two-dimensional
copper-copper bonding process}, booktitle={(Proceedings of 7th Electronics System-Integration
Technology Conference, Dresden, Germany)}, author={Dymel, Collin and Eichwald,
Paul and Schemmel, Reinhard and Hemsel, Tobias and Brökelmann, Michael and Hunstig,
Matthias and Sextro, Walter}, year={2018}, pages={1–6} }'
chicago: Dymel, Collin, Paul Eichwald, Reinhard Schemmel, Tobias Hemsel, Michael
Brökelmann, Matthias Hunstig, and Walter Sextro. “Numerical and Statistical Investigation
of Weld Formation in a Novel Two-Dimensional Copper-Copper Bonding Process.” In
(Proceedings of 7th Electronics System-Integration Technology Conference, Dresden,
Germany), 1–6, 2018.
ieee: C. Dymel et al., “Numerical and statistical investigation of weld formation
in a novel two-dimensional copper-copper bonding process,” in (Proceedings
of 7th Electronics System-Integration Technology Conference, Dresden, Germany),
2018, pp. 1–6.
mla: Dymel, Collin, et al. “Numerical and Statistical Investigation of Weld Formation
in a Novel Two-Dimensional Copper-Copper Bonding Process.” (Proceedings of
7th Electronics System-Integration Technology Conference, Dresden, Germany),
2018, pp. 1–6.
short: 'C. Dymel, P. Eichwald, R. Schemmel, T. Hemsel, M. Brökelmann, M. Hunstig,
W. Sextro, in: (Proceedings of 7th Electronics System-Integration Technology Conference,
Dresden, Germany), 2018, pp. 1–6.'
date_created: 2019-05-27T10:18:10Z
date_updated: 2020-05-07T05:33:56Z
department:
- _id: '151'
keyword:
- ultrasonic wire-bonding
- bond-tool design
- parameter identification
- statistical engineering
language:
- iso: eng
page: 1-6
project:
- _id: '93'
grant_number: MP-1-1-015
name: Hochleistungsbonden in energieeffizienten Leistungshalbleitermodulen
publication: (Proceedings of 7th Electronics System-Integration Technology Conference,
Dresden, Germany)
quality_controlled: '1'
status: public
title: Numerical and statistical investigation of weld formation in a novel two-dimensional
copper-copper bonding process
type: conference
user_id: '210'
year: '2018'
...
---
_id: '9876'
abstract:
- lang: eng
text: Piezoelectric inertia motors use the inertia of a body to drive it by means
of a friction contact in a series of small steps. It has been shown previously
in theoretical investigations that higher velocities and smoother movements can
be obtained if these steps do not contain phases of stiction (''stick-slip`` operation),
but use sliding friction only (''slip-slip`` operation). One very promising driving
option for such motors is the superposition of multiple sinusoidal signals or
harmonics. In this contribution, the theoretical results are validated experimentally.
In this context, a quick and reliable identification process for parameters describing
the friction contact is proposed. Additionally, the force generation potential
of inertia motors is investigated theoretically and experimentally. The experimental
results confirm the theoretical result that for a given maximum frequency, a signal
with a high fundamental frequency and consisting of two superposed sine waves
leads to the highest velocity and the smoothest motion, while the maximum motor
force is obtained with signals containing more harmonics. These results are of
fundamental importance for the further development of high-velocity piezoelectric
inertia motors.
author:
- first_name: Matthias
full_name: Hunstig, Matthias
last_name: Hunstig
- first_name: Tobias
full_name: Hemsel, Tobias
id: '210'
last_name: Hemsel
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Hunstig M, Hemsel T, Sextro W. High-velocity operation of piezoelectric inertia
motors: experimental validation. Archive of Applied Mechanics. 2014:1-9.
doi:10.1007/s00419-014-0940-0'
apa: 'Hunstig, M., Hemsel, T., & Sextro, W. (2014). High-velocity operation
of piezoelectric inertia motors: experimental validation. Archive of Applied
Mechanics, 1–9. https://doi.org/10.1007/s00419-014-0940-0'
bibtex: '@article{Hunstig_Hemsel_Sextro_2014, title={High-velocity operation of
piezoelectric inertia motors: experimental validation}, DOI={10.1007/s00419-014-0940-0},
journal={Archive of Applied Mechanics}, publisher={Springer Berlin Heidelberg},
author={Hunstig, Matthias and Hemsel, Tobias and Sextro, Walter}, year={2014},
pages={1–9} }'
chicago: 'Hunstig, Matthias, Tobias Hemsel, and Walter Sextro. “High-Velocity Operation
of Piezoelectric Inertia Motors: Experimental Validation.” Archive of Applied
Mechanics, 2014, 1–9. https://doi.org/10.1007/s00419-014-0940-0.'
ieee: 'M. Hunstig, T. Hemsel, and W. Sextro, “High-velocity operation of piezoelectric
inertia motors: experimental validation,” Archive of Applied Mechanics,
pp. 1–9, 2014.'
mla: 'Hunstig, Matthias, et al. “High-Velocity Operation of Piezoelectric Inertia
Motors: Experimental Validation.” Archive of Applied Mechanics, Springer
Berlin Heidelberg, 2014, pp. 1–9, doi:10.1007/s00419-014-0940-0.'
short: M. Hunstig, T. Hemsel, W. Sextro, Archive of Applied Mechanics (2014) 1–9.
date_created: 2019-05-20T13:08:08Z
date_updated: 2019-05-20T13:08:43Z
department:
- _id: '151'
doi: 10.1007/s00419-014-0940-0
keyword:
- Inertia motor
- High velocity
- Stick-slip motor
- Slip-slip operation
- Friction parameter identification
language:
- iso: eng
page: 1-9
publication: Archive of Applied Mechanics
publication_identifier:
issn:
- 0939-1533
publisher: Springer Berlin Heidelberg
status: public
title: 'High-velocity operation of piezoelectric inertia motors: experimental validation'
type: journal_article
user_id: '55222'
year: '2014'
...