Constitutive modelling of elastomer/graphene platelet nanocomposites

2017 International Conference on Materials and Intelligent Manufacturing

材料科学;机械制造

Abdelsalam, Amir A.^1 ; Araby, Sherif^2,3 ; Hassan, M.A.^1,4 ; El-Moneim, A.A.^1,5

Materials Science and Engineering Department, Egypt-Japan University of Science and Technology, Alexandria, Egypt^1

Department of Mechanical Engineering, Faculty of Engineering, Benha University, Egypt^2

School of Engineering, University of South Australia, SA

5095, Australia^3

Mechanical Engineering Department, Faculty of Engineering, Assiut University, Assiut

71516, Egypt^4

Physical Chemistry Dept., National Research Center, El-Dokki-Giza, Egypt^5

关键词: Deformation modeling;    Elastomeric materials;    Engineering applications;    Hyperelastic behavior;    Maximum relative errors;    Nonlinear elastics;    Numerical results;    Strain energy functions;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/244/1/012016/pdf
DOI  :  10.1088/1757-899X/244/1/012016

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

Elastomers are used in a wide variety of structural and engineering applications. They exhibit a nonlinear elastic stress-strain behaviour known as hyperelasticity which is generally described by hyperelastic strain energy functions. The question raised in the current study was; which model can accurately describe and predict the actual behaviour of the elastomer nanocomposites. The tensile data were used to fit the various elastomeric material models available in MSC.MARC finite element analysis package. The relative percentage error was calculated to determine the goodness of fit in order to select the best model. Numerical results showed that the third order deformation model was the best among the various material models since giving a maximum relative error of fit was 2.7% at small and large strains. To verify the effectiveness of third order deformation model, FE simulations for tensile test was carried out. The results showed that the third order model is sufficiently enough to regenerate the experimental data for uniaxial test and efficiently capture the hyperelastic behavior as good as the experiments.