Theoretical model predicts mechanical properties in composite materials under comprehensive compression, suggesting improved performance.
Purpose. The aim of the study is to theoretically substantiate the strength of domestic composite material under conditions of comprehensive compression and to create a model that allows predicting the behavior of the material underloads. Methodology. The study used the finite element method (FEM) to model the stress-strain state of the composite material. The experimental part included the preparation of multilayer specimens with polymer composite materials, their mechanical loading under conditions of comprehensive compression, and comparison of the results with the calculated data. Additionally, parametric modeling in the Ansys Workbench environment was used to study the effect of variables such as layer thickness and applied force. Findings. The dependencies between the thickness of the composite layer, the load, and the deformation characteristics of the material were obtained. The best mechanical properties were found in samples with a layer thickness of 2 mm, which demonstrate an optimal balance between strength and energy absorption. Modeling has shown that the highest stresses occur at the interface between the polymer layer and the metal substrate, indicating the need to improve the adhesive properties. Originality. A parametric model for analyzing the stress-strain state of polymeric composite materials is proposed. The methodology for assessing the strength of multilayer composites under conditions of comprehensive compression has been improved, which allows taking into account the interaction of layers and their geometric parameters. Practical value. The results of the study can be used to develop new composite materials with improved mechanical properties for use in the aviation, automotive, and energy industries. Recommendations for optimizing the thickness of layers and manufacturing technology will increase the durability and efficiency of composite structures.
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Bilodidenko et al. (2024) studied this question.
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