On efficient and reliable stochastic generation of RVEs for analysis of composites within the framework of homogenization

Salnikov, Vladimir; Choi, Daniel S.; Karamian-Surville, Philippe

doi:10.1007/s00466-014-1086-1

Cited by 21 publications

(31 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The classical RSA and the time-driven version of MD applied to generate the mixture of inclusions of spherical and cylindrical shapes will not be presented is this paper. A detailed description can be found in [7]. An example of a sample with a mixture of nonintersecting spherical and cylindrical inclusions is presented on the figure 1a.…”

Section: Rve Generation and Fft-based Homogenisationmentioning

confidence: 99%

On the Influence of the Inclusions’ Morphology on the Accuracy of the Prediction of Reinforced Composites Mechanical Behaviour

Hounkpati¹,

Salnikov²,

Karamian-Surville³

et al. 2016

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016)

Self Cite

View full text Add to dashboard Cite

Section: Rve Generation and Fft-based Homogenisationmentioning

confidence: 99%

On the Influence of the Inclusions’ Morphology on the Accuracy of the Prediction of Reinforced Composites Mechanical Behaviour

Hounkpati¹,

Salnikov²,

Karamian-Surville³

et al. 2016

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016)

Self Cite

View full text Add to dashboard Cite

“…We profit again from the MD-based method of generating the samples described in [7], namely from the table 1 there, which gives the expressions for repulsive forces between overlapping inclusions that depend on the geometry of overlaps. These forces, being rescaled appropriately, will characterize the resistance of the respective edge.…”

Section: Description Of the Methodsmentioning

confidence: 99%

“…Not going much into details, let us just say that the usual way out is to replace the inclusions by simple geometric objects and handle their repartition inside the sample. And certainly a lot of work has been done in this direction (see [7,8] and references therein).…”

Section: Stochastic Part -Sample Generationmentioning

confidence: 99%

“…Both algorithms have been adapted to the case of spherical and cylindrical inclusions and implemented in [7]. The input of the algorithms consists of the desired volume fraction, the respective number of spheres and cylinders and their geometric parameters.…”

Section: Stochastic Part -Sample Generationmentioning

confidence: 99%

“…We profit from the flexibility of the methods we have developped in [7,8] to use them in the analysis of electrical conductivity.…”

Section: Introduction / Motivationmentioning

confidence: 99%

See 2 more Smart Citations

Computation of effective electrical conductivity of composite materials: A novel approach based on analysis of graphs

Salnikov

Choi

Karamian-Surville

2018

Composite Structures

Self Cite

View full text Add to dashboard Cite

In this work we continue the investigation of different approaches to conception and modeling of composite materials. The global method we focus on, is called 'stochastic homogenization'. In this approach, the classical deterministic homogenization techniques and procedures are used to compute the macroscopic parameters of a composite starting from its microscopic properties. The stochastic part is due to averaging over some series of samples, and the fact that these samples fit into the concept of RVE (Representative Volume Element) in order to reduce the variance effect.In this article, we present a novel method for computation of effective electric properties of composites -it is based on the analysis of the connectivity graph (and the respective adjacency matrix) for each sample of a composite material. We describe how this matrix is constructed in order to take into account complex microscopic geometry. We also explain what we mean by homogenization procedure for electrical conductivity, and how the constructed matrix is related to the problem. The developed method is applied to a test study of the influence of micromorphology of composites materials on their conductivity.

show abstract

A Stochastic Analysis of the Damping Property of Filled Elastomers

Kulkarni

Tabarraei

2018

Macro Theory & Simulations

View full text Add to dashboard Cite

Finite elements modeling is used to investigate the damping property of Polymer composites consisting of a viscoelastic matrix and randomly dispersed elastic particles. The impact of vibration frequency, inclusions size and volume fraction on the damping capability of polymer composites are studied. It is shown that analytical micromechanics methods give accurate predictions only when inclusions volume fraction is small. The results show that loading frequency and inclusions volume fraction significantly impact the damping capability of polymer composites. The effect of domain boundary conditions on the simulation results is studied by conducting finite element modelings on representative volume elements (RVEs) which are subjected to periodic or mixed boundary conditions. The modeling results indicate that both boundary conditions lead to similar predictions for damping. Sensitivity analyses are conducted to assess how material properties influence the damping property. The sensitivity analyses show that an increase in the stiffness of the composite matrix leads to a reduction in the damping capability of polymer composites. In contrast, an increase in the stiffness of inclusions results in an increase in the damping capability of polymer composites. Moreover, the damping properties are improved if the relaxation time of the viscoelastic matrix is increased.

show abstract

On efficient and reliable stochastic generation of RVEs for analysis of composites within the framework of homogenization

Cited by 21 publications

References 22 publications

On the Influence of the Inclusions’ Morphology on the Accuracy of the Prediction of Reinforced Composites Mechanical Behaviour

On the Influence of the Inclusions’ Morphology on the Accuracy of the Prediction of Reinforced Composites Mechanical Behaviour

Computation of effective electrical conductivity of composite materials: A novel approach based on analysis of graphs

A Stochastic Analysis of the Damping Property of Filled Elastomers

Contact Info

Product

Resources

About