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 |
|
Kanit, Toufik
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (16/16 displayed)
- 2024Numerical study on the effects of yarn mechanical transverse properties on the ballistic impact behaviour of textile fabriccitations
- 2024Evaluation of the Relevance of Global and By-Step Homogenization for Composites and Heterogeneous Materials at Several Scales
- 2024Equivalent Morphology Concept in Composite Materials Using Machine Learning and Genetic Algorithm Couplingcitations
- 2023Effect of particles morphology on the effective elastic properties of bio–composites reinforced by seashells: Numerical investigationscitations
- 2023Effect of particles morphology on the effective elastic properties of bio–composites reinforced by seashells: Numerical investigationscitations
- 2022Effect of particles morphology on the effective elastic properties of bio–composites reinforced by seashells: Numerical investigationscitations
- 2021Microstructural features effect on the evolution of cyclic damage for polycrystalline metals using a multiscale approachcitations
- 2017Effective thermal and mechanical properties of randomly oriented short and long fiber compositescitations
- 2016Modeling of the effect of particles size, particles distribution and particles number on mechanical properties of polymer-clay nano-composites: Numerical homogenization versus experimental resultscitations
- 2016Effective transverse elastic properties of unidirectional fiber reinforced compositescitations
- 2016Random versus periodic microstructures for elasticity of fibers reinforced compositescitations
- 2013Computational homogenization of elastic-plastic compositescitations
- 2012Numerical study on the effects of yarn mechanical transverse properties on the ballistic impact behaviour of textile fabriccitations
- 2012Numerical study on the effects of yarn mechanical transverse properties on the ballistic impact behaviour of textile fabriccitations
- 2012Computational homogenization of elasto-plastic porous metalscitations
- 2006Apparent and effective physical properties of heterogeneous materials : representativity of samples of two materials from food industrycitations
Places of action
Organizations | Location | People |
---|
article
Computational homogenization of elastic-plastic composites
Abstract
This work describes a computational homogenization methodology to estimate the effective elastic-plastic response of random two-phase composite media. It is based on finite element simulations using three-dimensional cubic cells of different size but smaller than the deterministic representative volume element (DRVE) of the microstructure. We propose to extend the approach developed in the case of elastic heterogeneous media by Drugan and Willis (1996) and Kanit et al. (2003) to elastic-plastic composites. A specific polymer blend, made of two phases with highly contrasted properties, is selected to illustrate this approach; it consists of a random dispersion of elastic rubber spheres in an elastic-plastic glassy polymer matrix. It is found that the effective elastic-plastic response of this particulate composite can be accurately determined by computing a sufficient number of small subvolumes of fixed size extracted from the DRVE and containing different realizations of the random microstructure. In addition, the response of an individual subvolume is found anisotropic whereas the average of all subvolumes leads to recover the isotropic character of the DRVE. The necessary realization number to reach acceptable precision is given for two examples of particle volume fractions.