Uncorrelated volume element for stochastic modeling of microstructures based on local fiber volume fraction variation

Sanei, Seyed Hamid Reza; Fertig, Ray S.

doi:10.1016/j.compscitech.2015.06.010

Cited by 74 publications

(44 citation statements)

References 35 publications

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“…These results indicate that wt varies significantly with the size and location of the windows. Therefore choosing a relatively small RVE without considering local weight fraction variability can lead to unrealistic estimations of the effective mechanical behavior of composites [47,48,37].…”

Section: Computation Of Local Weight Fraction Variationmentioning

confidence: 99%

Effect of waviness and orientation of carbon nanotubes on random apparent material properties and RVE size of CNT reinforced composites

Savvas

Stefanou

Papadopoulos

et al. 2016

Composite Structures

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Section: Computation Of Local Weight Fraction Variationmentioning

confidence: 99%

Effect of waviness and orientation of carbon nanotubes on random apparent material properties and RVE size of CNT reinforced composites

Savvas

Stefanou

Papadopoulos

et al. 2016

Composite Structures

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“…This is clearly illustrated in the histograms where a very large variability of vf is observed for the sets containing windows of small size. Thus in the context of homogenization methods, choosing a RVE size for composite ma- terials with spatial randomness without considering local vf variability, can lead to unrealistic estimations of their mechanical behavior [23].…”

Section: Computation Of Local Volume Fraction Variationmentioning

confidence: 99%

Determination of Mesoscale Random Fields for the Apparent Properties of Spatially Random Composites

Savvas¹,

Stefanou²

2016

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

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“…It partitions an image in terms of pixel-based features into several homogeneous and disjoint regions so that the members within the same region share the same characteristics. Image segmentation is employed as a pre-processing step in many applications such as medical image processing [ 4 , 15 ] or modelling of microstructures [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

A Novel Image Segmentation Based on Clustering and Population-Based Optimisation

Mousavirad

Schaefer

Ebrahimpour-Komleh

et al. 2020

Lecture Notes in Computer Science

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Image segmentation is an essential step in image processing and computer vision with many image segmentation algorithms having been proposed in the literature. Among these, clustering is one of the prominent approaches to achieve segmentation. Traditional clustering algorithms have been used extensively for this purpose, although they have disadvantages such as dependence on initialisation conditions and a tendency to find only local optima. To overcome these disadvantages, population-based metaheuristic algorithms can be applied. In this paper, we propose a novel clustering algorithm based on human mental search (HMS) for image segmentation. HMS is a relatively new population-based metaheuristic inspired from the manner of searching in online auctions. HMS comprises three operators: mental search, which explores the neighbourhood of candidate solutions using Levy flight; grouping, which clusters candidate solutions; and moving candidate solutions towards a promising area. To verify the efficacy of the proposed algorithm, we conduct several experiments based on different criteria including mean cost function value, statistical analysis and image segmentation criteria. The obtained results confirm superior performance of our proposed algorithm compared to competitors.

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Uncorrelated volume element for stochastic modeling of microstructures based on local fiber volume fraction variation

Cited by 74 publications

References 35 publications

Effect of waviness and orientation of carbon nanotubes on random apparent material properties and RVE size of CNT reinforced composites

Effect of waviness and orientation of carbon nanotubes on random apparent material properties and RVE size of CNT reinforced composites

Determination of Mesoscale Random Fields for the Apparent Properties of Spatially Random Composites

A Novel Image Segmentation Based on Clustering and Population-Based Optimisation

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