| People | Locations | Statistics |
|---|---|---|
| Naji, M. |
| |
| Motta, Antonella |
| |
| Aletan, Dirar |
| |
| Mohamed, Tarek |
| |
| Ertürk, Emre |
| |
| Taccardi, Nicola |
| |
| Kononenko, Denys |
| |
| Petrov, R. H. | Madrid |
|
| Alshaaer, Mazen | Brussels |
|
| Bih, L. |
| |
| Casati, R. |
| |
| Muller, Hermance |
| |
| Kočí, Jan | Prague |
|
| Šuljagić, Marija |
| |
| Kalteremidou, Kalliopi-Artemi | Brussels |
|
| Azam, Siraj |
| |
| Ospanova, Alyiya |
| |
| Blanpain, Bart |
| |
| Ali, M. A. |
| |
| Popa, V. |
| |
| Rančić, M. |
| |
| Ollier, Nadège |
| |
| Azevedo, Nuno Monteiro |
| |
| Landes, Michael |
| |
| Rignanese, Gian-Marco |
|
Schneider, Matti
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (32/32 displayed)
- 2024Generation and analysis of digital twins for CoDiCoFRP accounting for fiber length and orientation distribution
- 2024Assumed strain methods in micromechanics, laminate composite voxels and level setscitations
- 2024Convergence of Damped Polarization Schemes for the FFT-Based Computational Homogenization of Inelastic Media With Pores
- 2024On the effectiveness of deep material networks for the multi-scale virtual characterization of short fiber-reinforced thermoplastics under highly nonlinear load casescitations
- 2024Generating microstructures of long fiber reinforced composites by the fused sequential addition and migration methodcitations
- 2023An orientation corrected shaking method for the microstructure generation of short fiber-reinforced composites with almost planar fiber orientationcitations
- 2023Accounting for weak interfaces in computing the effective crack energy of heterogeneous materials using the composite voxel technique
- 2023Homogenizing the viscosity of shear-thinning fiber suspensions with an FFT-based computational methodcitations
- 2023On fully symmetric implicit closure approximations for fiber orientation tensorscitations
- 2023Generation and analysis of digital twins for CoDiCoFRP accounting for fiber length and orientation distribution
- 2023On the Phase Space of Fourth-Order Fiber-Orientation Tensorscitations
- 2023Factors influencing the dynamic stiffness in short‐fiber reinforced polymers
- 2022On the impact of the mesostructure on the creep response of cellular NiAl-Mo eutecticscitations
- 2022Representative volume elements for matrix-inclusion composites - a computational study on periodizing the ensemblecitations
- 2022An algorithm for generating microstructures of fiber‐reinforced composites with long fibers
- 2022Probabilistic virtual process chain for process-induced uncertainties in fiber-reinforced composites
- 2022Multi-scale fatigue model to predict stiffness degradation in short-fiber reinforced composites
- 2022Solving phase-field models in the tensor train format to generate microstructures of bicontinuous compositescitations
- 2022A computational multiscale model for anisotropic failure of sheet molding compound composites
- 2022A sequential addition and migration method for generating microstructures of short fibers with prescribed length distribution
- 2022Accounting for viscoelastic effects in a multiscale fatigue model for the degradation of the dynamic stiffness of short-fiber reinforced thermoplastics
- 2022Identifying material parameters in crystal plasticity by Bayesian optimizationcitations
- 2021The sequential addition and migration method to generate representative volume elements for the homogenization of short fiber reinforced plasticscitations
- 2021An FE–DMN method for the multiscale analysis of short fiber reinforced plastic components
- 2021A multiscale high-cycle fatigue-damage model for the stiffness degradation of fiber-reinforced materials based on a mixed variational framework
- 2021Computing the effective crack energy of heterogeneous and anisotropic microstructures via anisotropic minimal surfaces
- 2021Identifying material parameters in crystal plasticity by Bayesian optimization
- 2021A computational multi-scale model for the stiffness degradation of short-fiber reinforced plastics subjected to fatigue loadingcitations
- 2020Computational homogenization of sheet molding compound composites based on high fidelity representative volume elementscitations
- 2019Material characterization and compression molding simulation of CF-SMC materials in a press rheometry testcitations
- 2017The sequential addition and migration method to generate representative volume elements for the homogenization of short fiber reinforced plasticscitations
- 2017Evaluating the Factors Influencing the Friction Behavior of Paperboard during the Deep Drawing Process
Places of action
| Organizations | Location | People |
|---|
article
An orientation corrected shaking method for the microstructure generation of short fiber-reinforced composites with almost planar fiber orientation
Abstract
We present an algorithm for generating short fiber-reinforced microstructures with almost planar fiber orientation. The orientation corrected shaking (OCS) method achieves a high accuracy regarding the volume fraction, fiber length distribution and fiber orientation state. Additionally, the algorithm is capable of generating microstructures for industrial materials, e.g., for a PA66GF35 material with a volume fraction of 19.3% and an aspect ratio of 33. For typical manufacturing processes, short fiber-reinforced composites show a mainly planar fiber arrangement. Therefore, we extend the two-step shaking algorithm of Li et al. [J. Ind. Text. 51(1), pp. 506–530, 2022] for a user-selected rectangular size of the unit cell and periodic boundary conditions. Additionally, the hidden closure structure of the algorithm is uncovered and a precise realization of the fiber orientation state achieved. We examine the representative volume element size for the OCS method, observing representative errors below 2% even for unit cells with edge lengths smaller than the mean fiber length. Additionally, the influence of different closure approximations on the stiffness is investigated. When applied to an industrial PA66GF35 material with sandwich structure, the OCS method demonstrates differences below 2% and 9% for the computed directional Young’s moduli $E_1$ and $E_2 $ compared to experimental data.