Abstract
The paper is devoted to an inverse problem of identification of individual material phases properties in dependence of known effective properties. In order to solve the identification problem, combining evolutionary algorithm with Mori-Tanaka method is proposed. In particular, the study focuses on a three-phase composite and takes experimental results from literature as an input data to analysis. The original contribution of this paper is a new identification strategy involving a resultant error that represents the uncertain character of both experimental data and model predictions. The new approach is demonstrated by performing several analyses with various assumptions. DOI: http://dx.doi.org/10.5755/j01.mech.22.5.16313
Highlights
Development of the novel composite materials leads to obtaining materials with unique properties, sometimes with characteristics opposite to the materials used as phases of the composite
There are a few works dealing with the identification of elastic constants of composite materials
Maletta and Pagnotta in work [1] and Beluch and Burczyński in work [2] combined finite element analysis with evolutionary algorithms in order to identify the elastic constants of composite laminates with the use of vibration test data
Summary
Development of the novel composite materials leads to obtaining materials with unique properties, sometimes with characteristics opposite to the materials used as phases of the composite. The main aim of this paper is connected with solving an inverse problem of identifying the individual material phases properties in dependence of known effective properties. Maletta and Pagnotta in work [1] and Beluch and Burczyński in work [2] combined finite element analysis with evolutionary algorithms in order to identify the elastic constants of composite laminates with the use of vibration test data. This study proposes to solve the identification problem with the use of evolutionary algorithms. Traditional identification methods, such as gradient methods, tend to stack in the local optima or cause problems with the calculation of fitness function gradient. Experimental data considered as input to analysis is based on results published in work of Duc and Minh [7]
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