Gradient-enhanced modelling of damage for rate-dependent material behaviour-a parameter identification framework
(2020) In Materials 13(14).- Abstract
The simulation of complex engineering components and structures under loads requires the formulation and adequate calibration of appropriate material models. This work introduces an optimisation-based scheme for the calibration of viscoelastic material models that are coupled to gradient-enhanced damage in a finite strain setting. The parameter identification scheme is applied to a self-diagnostic poly(dimethylsiloxane) (PDMS) elastomer, where so-called mechanophore units are incorporated within the polymeric microstructure. The present contribution, however, focuses on the purely mechanical response of the material, combining experiments with homogeneous and inhomogeneous states of deformation. In effect, the results provided lay the... (More)
The simulation of complex engineering components and structures under loads requires the formulation and adequate calibration of appropriate material models. This work introduces an optimisation-based scheme for the calibration of viscoelastic material models that are coupled to gradient-enhanced damage in a finite strain setting. The parameter identification scheme is applied to a self-diagnostic poly(dimethylsiloxane) (PDMS) elastomer, where so-called mechanophore units are incorporated within the polymeric microstructure. The present contribution, however, focuses on the purely mechanical response of the material, combining experiments with homogeneous and inhomogeneous states of deformation. In effect, the results provided lay the groundwork for a future extension of the proposed parameter identification framework, where additional field-data provided by the self-diagnostic capabilities can be incorporated into the optimisation scheme.
(Less)
- author
- Schulte, Robin ; Ostwald, Richard and Menzel, Andreas LU
- organization
- publishing date
- 2020
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Finite elements, Gradient-enhanced damage at large strains, Parameter identification, Rate-dependent material behaviour
- in
- Materials
- volume
- 13
- issue
- 14
- article number
- 3156
- publisher
- MDPI AG
- external identifiers
-
- pmid:32679825
- scopus:85088501323
- ISSN
- 1996-1944
- DOI
- 10.3390/ma13143156
- language
- English
- LU publication?
- yes
- id
- 1714e51d-7825-437e-9fc0-659886894c83
- date added to LUP
- 2020-08-04 11:46:50
- date last changed
- 2024-04-03 12:22:07
@article{1714e51d-7825-437e-9fc0-659886894c83,
abstract = {{<p>The simulation of complex engineering components and structures under loads requires the formulation and adequate calibration of appropriate material models. This work introduces an optimisation-based scheme for the calibration of viscoelastic material models that are coupled to gradient-enhanced damage in a finite strain setting. The parameter identification scheme is applied to a self-diagnostic poly(dimethylsiloxane) (PDMS) elastomer, where so-called mechanophore units are incorporated within the polymeric microstructure. The present contribution, however, focuses on the purely mechanical response of the material, combining experiments with homogeneous and inhomogeneous states of deformation. In effect, the results provided lay the groundwork for a future extension of the proposed parameter identification framework, where additional field-data provided by the self-diagnostic capabilities can be incorporated into the optimisation scheme.</p>}},
author = {{Schulte, Robin and Ostwald, Richard and Menzel, Andreas}},
issn = {{1996-1944}},
keywords = {{Finite elements; Gradient-enhanced damage at large strains; Parameter identification; Rate-dependent material behaviour}},
language = {{eng}},
number = {{14}},
publisher = {{MDPI AG}},
series = {{Materials}},
title = {{Gradient-enhanced modelling of damage for rate-dependent material behaviour-a parameter identification framework}},
url = {{http://dx.doi.org/10.3390/ma13143156}},
doi = {{10.3390/ma13143156}},
volume = {{13}},
year = {{2020}},
}