Algorithm of constructing hybrid effective modules for elastic isotropic composites

A. A. Svetashkov, J. Miciński, N. A. Kupriyanov, V. N. Barashkov, A. V. Lushnikov

Division for General Technical Subjects

Research output: Contribution to journal › Conference article

Abstract

The algorithm of constructing of new effective elastic characteristics of two-component composites based on the superposition of the models of Reiss and Voigt, Hashin and Strikman, as well as models of the geometric average for effective modules. These effective characteristics are inside forks Voigt and Reiss. Additionally, the calculations of the stress-strain state of composite structures with new effective characteristics give more accurate prediction than classical models do.

Original language	English
Article number	012095
Journal	IOP Conference Series: Materials Science and Engineering
Volume	177
Issue number	1
DOIs	https://doi.org/10.1088/1757-899X/177/1/012095
Publication status	Published - 1 Mar 2017
Event	10th International Conference on Mechanical Engineering, Automation and Control Systems 2016, MEACS 2016 - Tomsk, Russian Federation Duration: 27 Oct 2016 → 29 Oct 2016

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ASJC Scopus subject areas

Materials Science(all)
Engineering(all)

Cite this

Svetashkov, A. A., Miciński, J., Kupriyanov, N. A., Barashkov, V. N., & Lushnikov, A. V. (2017). Algorithm of constructing hybrid effective modules for elastic isotropic composites. IOP Conference Series: Materials Science and Engineering, 177(1), [012095]. https://doi.org/10.1088/1757-899X/177/1/012095

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AU - Barashkov, V. N.

AU - Lushnikov, A. V.

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AB - The algorithm of constructing of new effective elastic characteristics of two-component composites based on the superposition of the models of Reiss and Voigt, Hashin and Strikman, as well as models of the geometric average for effective modules. These effective characteristics are inside forks Voigt and Reiss. Additionally, the calculations of the stress-strain state of composite structures with new effective characteristics give more accurate prediction than classical models do.

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JF - IOP Conference Series: Materials Science and Engineering

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Access to Document

10.1088/1757-899X/177/1/012095