| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Ostwald, Richard
Helmut Schmidt University
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (10/10 displayed)
- 2024Enhancing damage prediction in bulk metal forming through machine learning-assisted parameter identificationcitations
- 2024Comparative Analysis of Phase-Field and Intrinsic Cohesive Zone Models for Fracture Simulations in Multiphase Materials with Interfaces: Investigation of the Influence of the Microstructure on the Fracture Properties
- 2022ADAPT — A Diversely Applicable Parameter Identification Tool: Overview and full-field application examplescitations
- 2021A computational framework for gradient‐enhanced damage
- 2020Prediction of ductile damage in the process chain of caliber rolling and forward rod extrusioncitations
- 2020Gradient-enhanced modelling of damage for rate-dependent material behaviour-a parameter identification frameworkcitations
- 2020Influence of anisotropic damage evolution on cold forgingcitations
- 2020Gradient-enhanced modelling of damage for rate-dependent material behaviour - a parameter identification framework
- 2020Prediction and analysis of damage evolution during caliber rolling and subsequent cold forward extrusioncitations
- 2015Modelling and simulation of phase transformations in elasto-plastic polycrystals
Places of action
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article
Gradient-enhanced modelling of damage for rate-dependent material behaviour-a parameter identification framework
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 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.