Homogenization of discrete mesoscale model of concrete for coupled mass transport and mechanics by asymptotic expansion

Eliáš, Jan; Cusatis, Gianluca

doi:10.1016/j.jmps.2022.105010

Cited by 14 publications

(2 citation statements)

References 71 publications

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“…In such a case, the mesoscale character of the model is crucial and hardly replaceable by tensorial homogeneous description. Reader is referred to recent paper [59] where homogenization of coupled mechanics and mass transport was developed for the discrete mesoscale model of concrete.…”

Section: Applicationmentioning

confidence: 99%

Homogenization of discrete diffusion models by asymptotic expansion

Eliáš

Yin

Cusatis

2022

Num Anal Meth Geomechanics

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Diffusion behaviors of heterogeneous materials are of paramount importance in many engineering problems. Numerical models that take into account the internal structure of such materials are robust but computationally very expensive. This burden can be partially decreased by using discrete models, however even then the practical application is limited to relatively small material volumes. This paper formulates a homogenization scheme for discrete diffusion models. Asymptotic expansion homogenization is applied to distinguish between (i) the continuous macroscale description approximated by the standard finite element method and (ii) the fully resolved discrete mesoscale description in a local representative volume element (RVE) of material. Both transient and steady‐state variants with nonlinear constitutive relations are discussed. In all the cases, the resulting discrete RVE problem becomes a simple linear steady‐state problem that can be easily pre‐computed. The scale separation provides a significant reduction of computational time allowing the solution of practical problems with a negligible error introduced mainly by the finite element discretization at the macroscale.

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Section: Applicationmentioning

confidence: 99%

Homogenization of discrete diffusion models by asymptotic expansion

Eliáš

Yin

Cusatis

2022

Num Anal Meth Geomechanics

Self Cite

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“…Mesoscale models are useful, not only to simulate processes at the mesoscale, but also to help parameterize and validate macroscale models. This can be done either by simple calibration or by use of sophisticated upscaling and homogenization techniques [8,9]. In addition, mesoscale models can also be used to propose phenomenological behavior laws that capture the impact of local processes [10].…”

Section: Introductionmentioning

confidence: 99%

From tomographic imaging to numerical simulations: an open-source workflow for true morphology mesoscale FE meshes

Cheikh Sleiman,

Moreira,

Tengattini

et al. 2024

RILEM Tech Lett

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Full-field techniques such as tomography are becoming progressively more central in the study of complex phenomena, in particular where spatiotemporal evolution is crucial, as in moisture transport or crack initiation in porous media. These techniques provide a unique insight in the local process whose quantification allows the improvement of our understanding and of the models describing them. Nevertheless, the model validation can be pushed further by attempting to explicitly represent the heterogeneities and simulate their role in the processes. Once validated, these models can be used to perform “virtual experiments”, and overcome the limitations of the experiments (e.g., sample size and number, fine control of the boundary and initial conditions). This study proposes a connection between tomography images and mesoscale models through a workflow that mainly employs open-source tools. This workflow is illustrated through the digitization of a Portland cement concrete sample, stemming from neutron tomographies and resulting in a numerical finite element mesh. The proposed workflow is flexible, allowing for the conversion of images from various sources, such as x-ray or neutron tomographies, to different numerical representations of the domain, such as finite element meshes or even a discrete domain required by discrete element methods, while preserving real morphologies with an accuracy proportionate to the specific need of the problem. Beside its generalizability, our method also offers automated labelling of the different domains and boundaries in both the volumetric and surface meshes, which is often necessary for assigning material properties and boundary conditions. Finally, the series of image, geometry and mesh processing steps described in this work are made available on a GitHub repository.

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