• Aucun résultat trouvé

An Adaptive Multiscale Strategy to Simulate Fracture of Composite Structures

N/A
N/A
Protected

Academic year: 2021

Partager "An Adaptive Multiscale Strategy to Simulate Fracture of Composite Structures"

Copied!
1
0
0

Texte intégral

(1)

The Third International Conference on Computational Modeling of Fracture and Failure of Materials and Structures

An Adaptive Multiscale Strategy to Simulate Fracture of Composite Structures

A. Akbari R.

, P. Kerfriden, S. Bordas

Institute of Mechanics and Advanced Materials, School of Engineering, Cardiff University, Queen’s Buildings, The Parade, Cardiff CF24 3AA Wales, UK. akbarirahimabadia@cardiff.ac.uk In order to simulate fracture in composite structures,

one of the most promising approaches is to model the behaviour of the material at the scale of the ma- terial heterogeneities, which is usually called micro or meso-modelling. In a second step, these fine-scale features can be transferred to the scale of the struc- ture by averaging techniques (on representative vol- ume element or unit cells) or homogenisation. How- ever, in the case of fracture, these upscaling methods cannot be used in the vicinity of cracks, as the sepa- ration of scales necessary for their application is lost.

In the literature, two schools of thought aim at alle- viating this problem. The first one tries to extend the applicability of averaging techniques to fracture (e.g.

reference [5] for special averaging techniques dedi- cated to established damage bands). The second one aims at analysing the zones where homogenisation fails directly at the microscopic scale (e.g. [2, 3]), in a concurrent framework (i.e. domain decompo- sition). Although the latter approach is more gen- eral, it is heavier in terms of computations, and re- quires the development of robust adaptivity proce- dures [3, 4, 6], which is the topic of this contribution.

We propose to capture the initiation of the dam- age mechanisms at the macroscale using a classi- cal FE2 approach [1]. In order to control the preci- sion of the simulations, an error estimation for the upscaling strategy is carried out at each step of the time integration algorithm. Based on this estima- tion, the macro elements are refined hierarchically where needed. When the size of a macro-element becomes of the order of the statistical volume ele- ment used in the FE2 method, the homogenisation step is bypassed. Instead, the corresponding process zone is modelled directly at the microscale and cou- pled to the homogenised region by a mortar-type glu- ing technique. In the presentation, we will emphasise some key points of the adaptive multiscale method, including:

- the error estimation technique for the chosen up- scaling method

- the transfer of internal variables when adapting the macroscopic mesh

- the arc-length method, defined over multiple scales, allowing to regularise softening problems that are treated in quasi-statics.

The efficiency of the method will be demonstrated on examples of fracture in polycrystalline materials, for which the damage mechanisms are represented by intragranular plasticity and intergranular cohesive debonding.

References

[1] F. Feyel and J. Chaboche. FE

2

multiscale ap- proach for modelling the elastoviscoplastic be- haviour of long fibre SiC/Ti composite materi- als. Comp. Meth. Appl. Mech. Engrg., 183:309–

330, 2000.

[2] P. Kerfriden, O. Allix, and P. Gosselet. A three- scale domain decomposition method for the 3D analysis of debonding in laminates. Computa- tional Mechanics, 44(3):343–362, 2009.

[3] F. Larsson and K. Runesson. On two-scale adaptive FE analysis of micro-heterogeneous media with seamless scale-bridging. Comp.

Meth. Appl. Mech. Engrg., 200(37-40):2662–

2674, 2011.

[4] O. Lloberas-Valls, D. J. Rixen, A. Simone, and L. J. Sluys. Multiscale domain decomposition analysis of quasi-brittle heterogeneous materi- als. Int. J. Num. Meth. Engrg, 89:1337–1366, 2012.

[5] V. P. Nguyen, O. Lloberas-valls, M. Stroeven, and L. J. Sluys. Computational homogeniza- tion for multiscale crack modeling. Implemen- tational and computational aspects. Int. J. Num.

Meth. Engrg., 89:192–226, 2012.

[6] A. Romkes, J. T. Oden, and K. Vemaganti.

Multi-scale goal-oriented adaptive modeling of random heterogeneous materials. Mechanics of Materials, 38(8-10):859–872, 2006.

CFRAC 2013 Prague, Czech Republic, 5–7 June 2013

Références

Documents relatifs

c) Factors controlling hematopoiesis ... Genetic interaction between Drosophila melanogaster and Leptopilina boulardi ... Fly resistance ... Parasitoid virulence factors ...

We then consider algebraic model reduction, namely the proper orthogonal decomposi- tion(POD) to drastically reduce the computational time associated with computing the response

Figure 5.27 – Approximation géométrique d’une microstructure contenant des

Engineering  &  Medical  Mul/scale  Problems  -­‐  fracture  &   cu8ng.. Surgical simulation

This method is set in the context of FE 2 [20] for which computational ho- mogenisation breaks down upon loss of material stability (softening). The lack of scale separation due to

Discrete materials such as 3D printed structures, paper, textiles, foams, or concrete, can be successfully modelled by lattice structures, which are especially suited for

The amplitude and phase of the modulation depend on the neutrino ’s mass, as well as the fraction of cosmic neutrinos that are bound versus unbound to the Galaxy.. For a neutrino

The tufted plates subjected to short-beam shear tests aided especially in the behavior analysis of tufting density and angle in mode II loading condition, while