Computational micromechanics of porous brittle solids

Blatny, Lars; Löwe, Henning; Wang, Stephanie; Gaume, Johan

doi:10.1016/j.compgeo.2021.104284

Cited by 10 publications

(5 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The cap depends on

{\varepsilon }_{v}^{p}

, particularly

{p}_{c}={p}_{c}\left(\zeta ,{\varepsilon }_{v}^{p}\right)=-c{e}^{-\zeta {\varepsilon }_{v}^{p}}

, where c > 0 is the cohesion (or tensile strength) of the undamaged material and ζ > 0 gives the degree of postyield softening. Thus, initially, p c = − c , then with accumulating volumetric plastic strain, p c increases toward zero naturally leading to material separation (Blatny et al., 2021, 2023; Klár et al., 2016; Stomakhin et al., 2013; Wolper et al., 2019, 2021). For more details on the numerical scheme and the elastoplastic law, please refer Supporting Information .…”

Section: Methodsmentioning

confidence: 99%

Transition Between Mechanical and Geometric Controls in Glacier Crevassing Processes

Rousseau,

Gaume,

Blatny

et al. 2024

Geophysical Research Letters

Self Cite

View full text Add to dashboard Cite

Herein, fast fracture initiation in glacier ice is modeled using a Material Point Method and a simplified constitutive law describing tensile strain softening. Relying on a simple configuration where ice flows over a vertical step, crevasse patterns emerge and are consistent with previous observations reported in the literature. The model’s few parameters allows identification of a single dimensionless number controlling fracture spacing and depth. This scaling law delineates two regimes. In the first one, ice thickness does not play a role and only ice tensile strength controls the spacing, giving rise to numerous surface crevasses, as observed in crevasse fields. In this regime, scaling can recover classical values for ice tensile strength from macroscopic field observations. The second regime, governed by ice bending, produces large‐scale, deep fractures resembling serac falls or calving events.

show abstract

“…The cap depends on

{\varepsilon }_{v}^{p}

, particularly

{p}_{c}={p}_{c}\left(\zeta ,{\varepsilon }_{v}^{p}\right)=-c{e}^{-\zeta {\varepsilon }_{v}^{p}}

Section: Methodsmentioning

confidence: 99%

Transition Between Mechanical and Geometric Controls in Glacier Crevassing Processes

Rousseau,

Gaume,

Blatny

et al. 2024

Geophysical Research Letters

Self Cite

View full text Add to dashboard Cite

show abstract

“…Alternative methods of generating random porous structures may be based on random fractals such as Appollonian packings [14] or on level-cutting random fields, see e.g. the use of thresholded Gaussian random fields for modelling snow microstructures [15]. For this study we considered structures of three different sizes ranging from L = 50 mm over 100 mm up to 200 mm.…”

Section: Geometry Generationmentioning

confidence: 99%

Effects of disorder on deformation and failure of brittle porous materials

Ritter¹,

Shegufta²,

Zaiser³

2023

Preprint

View full text Add to dashboard Cite

The mechanical behavior of porous materials depends strongly on porosity and pore geometry, but also on morphological parameters characterizing the spatial arrangement of pores. Here we use bond-based peridynamics to study effects of disorder on the deformation and failure behavior of brittle porous solids both in the quasi-static limit and in case of dynamic loading scenarios. We show that structural disorder, which has a strong influence on stiffness, strength and toughness in the quasi-static limit, becomes less relevant under dynamic loading conditions.

show abstract

“…Alternative methods of generating random porous structures may be based on random fractals such as Appollonian packings [14] or on level-cutting random fields, see e.g. the use of thresholded Gaussian random fields for modeling snow microstructures [15]. For this study, we considered structures of three different sizes, ranging from L = 50 mm over 100 mm up to 200 mm.…”

Section: Geometry Generationmentioning

confidence: 99%