2015
DOI: 10.1080/14786435.2015.1061716
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Scale selection in nonlinear fracture mechanics of heterogeneous materials

Abstract: A new adaptive multiscale method for the nonlinear fracture simulation of heterogeneous materials is proposed. The two major sources of error in the finite element simulation are discretisation and modelling errors. In the failure problems, the discretisation error increases due to the strain localisation which is also a source for the error in the homogenisation of the underlying micro-structure. In this paper, the discretisation error is controlled by an adaptive mesh refinement procedure following the Zienk… Show more

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Cited by 23 publications
(11 citation statements)
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References 53 publications
(69 reference statements)
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“…The interested reader is referred to the work of Kerfriden and coworkers and the publications therein, where Newton–Krylov [ 23 ], local–global [ 24 ] domain-wise model order reduction [ 25 ], and Bayesian approaches [ 26 ] are proposed. Those algebraic-based model order reduction techniques may be complemented by multiscale approaches, as in [ 27 ], where a scale-selection approach is proposed for determining the optimal model for a given region. Finally, statistical-based approaches have been proposed [ 28 ] in order to determine the fracture process zone based on the lack of ability of reduced order models to represent the failure of the system.…”
Section: Introductionmentioning
confidence: 99%
“…The interested reader is referred to the work of Kerfriden and coworkers and the publications therein, where Newton–Krylov [ 23 ], local–global [ 24 ] domain-wise model order reduction [ 25 ], and Bayesian approaches [ 26 ] are proposed. Those algebraic-based model order reduction techniques may be complemented by multiscale approaches, as in [ 27 ], where a scale-selection approach is proposed for determining the optimal model for a given region. Finally, statistical-based approaches have been proposed [ 28 ] in order to determine the fracture process zone based on the lack of ability of reduced order models to represent the failure of the system.…”
Section: Introductionmentioning
confidence: 99%
“…This enables the coarsening of the mesh if the discretization error is unnecessarily small in comparison to the modeling error as is done, e.g. in [5] and [120,23,121,118,122] for adaptive scale selection. Conversely, for specific applications where modeling errors are small or moderate, the mesh can be refined efficiently to increase the precision.…”
Section: Applicability For Patient-specific Biomechanics?mentioning
confidence: 99%
“…With increasing computational power, numerical models that fully resolve the microstructural geometry in the whole macroscopic domain, e.g. [5,6], or in regions of interest [7,8], have emerged, addressing problems without clear scale separation.…”
Section: Introductionmentioning
confidence: 99%
“…Influence of morphing operations on resulting (a) two-and (b) three-dimensional geometry. From the original particle distribution (depicted with light grey), the closed-cell, foam-like geometry (shown in blue) is obtained by Eq (7). and the open-like features (plotted in red) follow from Eq (8)…”
mentioning
confidence: 99%