Using Genetic Algorithm for Investigating the Performance of Carbonbasalt/ Polyester Hybrids Composite Materials

Author(s): Mohammed Belkheir, Bendouma Doumi*, Allel Mokaddem*, Ahmed Boutaous

Journal Name: Current Materials Science
Formerly Recent Patents on Materials Science

Volume 13 , Issue 2 , 2020

Become EABM
Become Reviewer

Graphical Abstract:


Abstract:

Background: The composite materials are more efficient and more resistant compared to so-called traditional materials. The application of continuous and variable forces modifies the properties of the materials, and generates the formation of cracks which lead to the rupture of structures.

Objective: The objective of this work is to study the reliability and the origin of the resistance of each fiber-matrix interface of the two hybrid composite materials studied.

Methods: In this study, the genetic algorithm is based on Weibull’s probabilistic approach to calculate the damage to the interface and also on the Cox model to find and initialize the different values used in simulation model.

Results: The results obtained by genetic modeling, have shown that the hybrid Carbon High Modulus (HM)/Basalt/Polyester composite is the most resistant to the mechanical stresses applied comparing with that of Carbon High Strength (HS)/Basalt/Polyester. These results were confirmed by the level of damage to the interface found for the two materials studied and that the interface shear damage of the hybrid Carbon HM/Basalt/Polyester composite is much lower by 13% compared to that of Carbon HS/Basalt/Polyester.

Conclusion: The calculations are in good agreement with the analytical results of Cox, where he demonstrated that Young’s modulus of the fibers has an important influence on the shear strength of the fiber/matrix interface of composite materials.

Keywords: Damage, carbon HM, HS, polyester, basalt, hybrid composites.

Rights & PermissionsPrintExport Cite as

Article Details

VOLUME: 13
ISSUE: 2
Year: 2020
Published on: 15 January, 2021
Page: [120 - 128]
Pages: 9
DOI: 10.2174/2666145413999201124224238
Price: $65

Article Metrics

PDF: 7