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非连续增强复合材料组分弹性性能的反识别

Inverse Identification of Elastic Properties of Constituents of Discontinuously Reinforced Composites.

作者信息

Ogierman Witold

机构信息

Institute of Computational Mechanics and Engineering, Faculty of Mechanical Engineering, Silesian University of Technology, Konarskiego 18A, 44-100 Gliwice, Poland.

出版信息

Materials (Basel). 2018 Nov 20;11(11):2332. doi: 10.3390/ma11112332.

Abstract

This paper is devoted to determination of elastic properties of composite constituents by using an inverse identification procedure. The aim of the developed identification procedure is to compute the elastic constants of individual material phases on the basis of known properties of composite materials. The inverse problem of identification has been solved by combining an evolutionary algorithm with a micromechanical model. The paper also focuses on selection of a suitable micromechanical model for optimization which should ensure a compromise between accuracy and complexity. Two different cases have been studied: composite reinforced with short cylindrical fibers and composite reinforced with cubic particles. Moreover, Monte Carlo simulations have been carried out to expose a difference in outcome of identification which may occur when uncertain input data is considered. Obtained results show that identification is successful only when properties of composite materials with at least two different volume fractions of the reinforcement are known.

摘要

本文致力于通过使用逆识别程序来确定复合材料组分的弹性特性。所开发的识别程序的目的是根据复合材料的已知特性来计算各个材料相的弹性常数。通过将进化算法与微观力学模型相结合,解决了识别的逆问题。本文还着重于选择适合优化的微观力学模型,该模型应在准确性和复杂性之间取得平衡。研究了两种不同情况:短圆柱纤维增强复合材料和立方颗粒增强复合材料。此外,进行了蒙特卡洛模拟,以揭示在考虑不确定输入数据时可能出现的识别结果差异。所得结果表明,只有当已知具有至少两种不同增强体体积分数的复合材料的特性时,识别才会成功。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a76/6266842/840f5052778e/materials-11-02332-g001.jpg

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