Numerical Characterization of Concrete Heterogeneity

Pitangueira, Roque Luiz da Silva; Silva, Raul Rosas e

doi:10.1590/s1516-14392002000300015

Cited by 3 publications

(2 citation statements)

References 6 publications

(6 reference statements)

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“…Although lacking of predictability, the authors concluded that the model is suitable for rock mechanics. A statistical approach for modelling heterogeneous concrete, where the different phases were represented by a statistical distribution of constituent phases, has previously been developed within the framework of FEM [36]. For heterogeneous material a combined FEM and a nonlinear cohesive model to simulate compacted metal powder was presented and validated in [21].…”

Section: Introductionmentioning

confidence: 99%

A statistical DEM approach for modelling heterogeneous brittle materials

et al. 2021

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By utilizing numerical models and simulation, insights about the fracture process of brittle heterogeneous materials can be gained without the need for expensive, difficult, or even impossible, experiments. Brittle and heterogeneous materials like rocks usually exhibit a large spread of experimental data and there is a need for a stochastic model that can mimic this behaviour. In this work, a new numerical approach, based on the Bonded Discrete Element Method, for modelling of heterogeneous brittle materials is proposed and evaluated. The material properties are introduced into the model via two main inputs. Firstly, the grains are constructed as ellipsoidal subsets of spherical discrete elements. The sizes and shapes of these ellipsoidal subsets are randomized, which introduces a grain shape heterogeneity Secondly, the micromechanical parameters of the constituent particles of the grains are given by the Weibull distribution. The model was applied to the Brazilian Disc Test, where the crack initiation, propagation, coalescence and branching could be investigated for different sets of grain cement strengths and sample heterogeneities. The crack initiation and propagation was found to be highly dependent on the level of heterogeneity and cement strength. Specifically, the amount of cracks initiating from the loading contact was found to be more prevalent for cases with higher cement strength and lower heterogeneity, while a more severe zigzag shaped crack pattern was found for the cases with lower cement strength and higher heterogeneity. Generally, the proposed model was found to be able to capture typical phenomena associated with brittle heterogeneous materials, e.g. the unpredictability of the strength in tension and crack properties.

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Section: Introductionmentioning

confidence: 99%

A statistical DEM approach for modelling heterogeneous brittle materials

et al. 2021

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“…Composite structures have a peculiar behavior, justified by their heterogeneity 2 . In this context, reinforced concrete structures, when subjected to any thermal variations, might have their performance altered mainly due to the concrete components 3,4 , which includes the loss of bearing capacity and/or structural performance.…”

Section: Introductionmentioning

confidence: 99%

Bifurcation Analysis of Columns of Composite Materials with Thermal Variation

Wahrhaftig

Magalhães

2021

Mat. Res.

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Stochastic inverse finite element modeling for characterization of heterogeneous material properties

Llopis-Albert

Rubio

Valero

et al. 2019

Mater. Res. Express

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The micro and meso-structural characteristics of materials present an inherent variability because of the intrinsic scatter in raw material and manufacturing processes. This problem is exacerbated in highly heterogeneous materials, which shows significant uncertainties in the macroscale material properties. Therefore, providing optimal designs and reliable structural analyses strongly depend on the selection of the underlying material property models. This paper is intended to provide insight into such a dependence by means of a stochastic inverse model based on an iterative optimization process depending only of one parameter, thus avoiding complex parametrizations. It relies on non-linear combinations of material property realizations with a defined spatial structure for constraining stochastic simulations to data within the framework of a Finite Element approach. In this way, the procedure gradually deforms unconditional material property realizations to approximate the reproduction of information including mechanical parameters (such as Young's modulus and Poisson's ratio fields) and variables (e.g., stress and strain fields). It allows dealing with non-multiGaussian structures for the spatial structure of the material property realizations, thus allowing to reproduce the coalescence and connectivity among phases and existing crack patterns that often take place in composite materials, being these features crucial in order to obtain more reliable safety factors and fatigue life predictions. The methodology has been successfully applied for the characterization of a complex case study, where an uncertainty assessment has been carried out by means of multiple equally likely realizations.

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Numerical Characterization of Concrete Heterogeneity

Cited by 3 publications

References 6 publications

A statistical DEM approach for modelling heterogeneous brittle materials

A statistical DEM approach for modelling heterogeneous brittle materials

Bifurcation Analysis of Columns of Composite Materials with Thermal Variation

Stochastic inverse finite element modeling for characterization of heterogeneous material properties

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