Computational Strategy for Analyzing Effective Properties of Random Composites—Part I: Conductivity

The notion of “randomness” in the mathematical theory of composites has typically been used abstractly within measure theory, making practical applications difficult. In contrast, engineering sciences often discuss randomness too loosely, lacking a theoretical foundation. This paper aims to bridge the gap between theory and applications, focusing on the effective properties of two-dimensional conducting composites with non-overlapping circular inclusions. It is shown that there is no universal minimum number of inclusions per cell in simulations of random composites. Even minor changes to Random Sequential Addition algorithms lead to different formulas for the effective constants. Application of the analytical representative volume element (aRVE) theory methodologically and practically addresses the diversity issue of random composites based on homogenization principles. In particular, it examines how the spatial arrangement of inclusions impacts the overall composite properties. The proposed method can be applied to a large number of inclusions and to symbolically given geometric and physical parameters relevant to optimal design problems. The method leverages structural sums and enables a more refined classification of different classes of composites, which was unattainable using previous approaches. The obtained results demonstrate a diversity of apparently similar composites. This paper outlines the investigation strategy and provides a detailed description of each step.

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Publication Details

Journal
Applied Sciences
Published
2025-04-01
DOI
https://doi.org/10.3390/app15073861
Citations
3
Primary Topic
Composite Material Mechanics
Type
article
Field-Weighted Citation Impact
2.59
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article

Computational Strategy for Analyzing Effective Properties of Random Composites—Part I: Conductivity

Vladimir Mityushev, S. Gluzman, N. Zh. Nauryzbayev, Karlygash Nurtazina et al.
3 citations
Applied Sciences
Composite Material Mechanics
2.59
article

Computational Strategy for Analyzing Effective Properties of Random Composites—Part I: Conductivity

Vladimir Mityushev, S. Gluzman, N. Zh. Nauryzbayev, Karlygash Nurtazina, Piotr Drygaś
article en
3 citations

Abstract

The notion of “randomness” in the mathematical theory of composites has typically been used abstractly within measure theory, making practical applications difficult. In contrast, engineering sciences often discuss randomness too loosely, lacking a theoretical foundation. This paper aims to bridge the gap between theory and applications, focusing on the effective properties of two-dimensional conducting composites with non-overlapping circular inclusions. It is shown that there is no universal minimum number of inclusions per cell in simulations of random composites. Even minor changes to Random Sequential Addition algorithms lead to different formulas for the effective constants. Application of the analytical representative volume element (aRVE) theory methodologically and practically addresses the diversity issue of random composites based on homogenization principles. In particular, it examines how the spatial arrangement of inclusions impacts the overall composite properties. The proposed method can be applied to a large number of inclusions and to symbolically given geometric and physical parameters relevant to optimal design problems. The method leverages structural sums and enables a more refined classification of different classes of composites, which was unattainable using previous approaches. The obtained results demonstrate a diversity of apparently similar composites. This paper outlines the investigation strategy and provides a detailed description of each step.

Applied SciencesVol. 15(7)
L. N. Gumilyov Eurasian National University (KZ), Cracow University of Technology (PL)
Openalex Percentile: Top 12%
Composite Material Mechanics
2.59
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Computational Strategy for Analyzing Effective Properties of Random Composites—Part I: Conductivity — Vladimir Mityushev, S. Gluzman, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS