Modelling the microstructure of concrete with spherical grains

Ballani, Felix; Daley, D. J.; Stoyan, Dietrich

doi:10.1016/j.commatsci.2005.03.005

Cited by 29 publications

(20 citation statements)

References 27 publications

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“…granular porous media or foams. Boolean models can be fitted to sandstone samples [3], open foams can be described using the edge system of random tessellations [15], concrete by random packings of spheres [4], sinter structures as random tessellations. In most cases the suitable models can not be described using few parameters and model fitting is restricted to "trial and error".…”

Section: Discussionmentioning

confidence: 99%

Design of acoustic trim based on geometric modeling and flow simulation for non-woven

Schladitz¹,

Peters²,

Reinel-Bitzer³

et al. 2006

Computational Materials Science

196

118

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In order to optimize the acoustic properties of a stacked fiber nonwoven, the microstructure of the non-woven is modeled by a macroscopically homogeneous random system of straight cylinders (tubes). That is, the fibers are modeled by a spatially stationary random system of lines (Poisson line process), dilated by a sphere. Pressing the non-woven causes anisotropy. In our model, this anisotropy is described by a one parametric distribution of the direction of the fibers. In the present application, the anisotropy parameter has to be estimated from 2d reflected light microscopic images of microsections of the non-woven.After fitting the model, the flow is computed in digitized realizations of the stochastic geometric model using the lattice Boltzmann method. Based on the flow resistivity, the formulas of Delany and Bazley predict the frequency-dependent acoustic absorption of the non-woven in the impedance tube.Using the geometric model, the description of a non-woven with improved acoustic absorption properties is obtained in the following way: First, the fiber thicknesses, porosity and anisotropy of the fiber system are modified. Then the flow and acoustics simulations are performed in the new sample. These two steps are repeatedc for various sets of parameters. Finally, the set of parameters for the geometric model leading to the best acoustic absorption is chosen.

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Section: Discussionmentioning

confidence: 99%

Design of acoustic trim based on geometric modeling and flow simulation for non-woven

Schladitz¹,

Peters²,

Reinel-Bitzer³

et al. 2006

Computational Materials Science

196

118

View full text Add to dashboard Cite

show abstract

“…The forcebiased (FB) algorithm (Moscinski et al, 1989;Moscinski and Bargiel, 1991;Bezrukov et al, 2002) has been one of the most commonly used ways of generating random close packings of balls. Two particular applications of which are the modelling of the microstructure of concrete (Ballani et al, 2006) and sintered copper (Lautensack et al, 2006). In both of these cases FB generates dense isotropic packings with patterns that are too regular compared to the data even when random shifts of balls are introduced in order to disturb the regularity.…”

Section: High-intensity Packingmentioning

confidence: 99%

Spatial—temporal marked point processes: a spectrum of stochastic models

Renshaw¹

2009

Environmetrics

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SUMMARYMany processes that develop through space and time do so in response not only to their own individual growth mechanisms but also in response to interactive pressures induced by their neighbours. The growth of trees in a forest which compete for light and nutrient resources, for example, provides a classic illustration of this general spatialtemporal growth-interaction process. Not only has its mathematical representation proved to be a powerful tool in the study and analysis of marked point patterns since it may easily be simulated, but it has also been shown to be highly flexible in terms of its application since it is robust with respect to incorrect choice of model selection. Moreover, it is highly amenable to maximum likelihood and least squares parameter estimation techniques. Currently the algorithm comprises deterministic growth and interaction coupled with a stochastic arrival and departure mechanism. So for systems with a fixed number of particles there is an inherent lack of randomness. A variety of different stochastic approaches are therefore presented, from the exact event-time model through to the associated stochastic differential equation, taking in time-increment and Tau-and Langevin-Leaping approximations en route. The main algorithm is illustrated through application to forest management and high-intensity packing of hard particle systems, and comparisons are made with the established force biased approach.

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“…The work of Rollett et al [8,9] made significant improvements on the ability to generate virtual 3D microstructures. This methodology is linked to real microstructures through the collection of statistical distributions of grain size and shape in 2D.…”

Section: Introductionmentioning

confidence: 99%

A framework for automated 3D microstructure analysis & representation

Groeber

Uchic

Dimiduk

et al. 2007

J Computer-Aided Mater Des

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Over the past 5 years there have been significant advances in developing serial-sectioning methods that provide quantitative data describing the structure and crystallography of grain-level microstructures in three dimensions (3D). The subsequent analysis and representation of this information can provide modeling and simulation efforts with a highly-refined and unbiased characterization of specific microstructural features. For example, the grain structure and crystallography of an engineering alloy could be characterized and then translated directly into a 3D volume mesh for subsequent Finite Element Analysis. However, this approach requires a multitude of data sets in order to appropriately sample the intrinsic heterogeneity observed in typical microstructures. One way to circumvent this issue is to develop computation tools that create synthetic microstructures that are statisticallyequivalent to the measured structure. This study will discuss the development of software programs that take as input a series of Electron Backscatter Diffraction Patterns from a serial sectioning experiment, and output a robust statistical analysis of the 3D data, as well as generate a host of synthetic structures which are analogous to the real microstructure. Importantly, the objective of this study is to provide a framework towards complete microstructure representation that is consistent with quantifiable experimental data.

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Modelling the microstructure of concrete with spherical grains

Cited by 29 publications

References 27 publications

Design of acoustic trim based on geometric modeling and flow simulation for non-woven

Design of acoustic trim based on geometric modeling and flow simulation for non-woven

Spatial—temporal marked point processes: a spectrum of stochastic models

A framework for automated 3D microstructure analysis & representation

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