Title: Elastic and thermal property studies of CNT reinforced epoxy composite with waviness, agglomeration and interphase effects
Authors: Puneet Kumar; J. Srinivas
Addresses: Mechanical Engineering Department, National Institute of Technology Rourkela, Odisha, India ' Mechanical Engineering Department, National Institute of Technology Rourkela, Odisha, India
Abstract: This paper presents an effective approach of predicting the elastic and thermal properties of carbon nanotube (CNT) reinforced epoxy nanocomposite material. Modified Halpin-Tsai (HT) and effective medium approximation (EMA) models are proposed for predicting the elastic modulus and thermal conductivity of composite. Waviness, interphase and agglomeration are modelled as influencing factors in terms of basic geometric and processing characteristics of CNTs and introduced in conventional models without loss of generality. The results obtained from modified models indicate that proposed models can precisely predict the resultant elastic modulus and thermal conductivity by accounting CNT characteristics and also shows the nonlinear behaviour at high CNT content. After validating the results, the most influencing characteristics are identified by means of analysis of variance (ANOVA) approach. A three-layer backpropagation neural network is used to generalise the relationship between the most influencing input and output variables. This intelligent material modelling technique provides reasonable values of elastic modulus and thermal conductivities over a wide range of input parameters.
Keywords: carbon nanotubes; Halpin-Tsai model; material modelling; reinforcement characteristics; neural networks.
International Journal of Materials Engineering Innovation, 2018 Vol.9 No.2, pp.158 - 177
Received: 02 Aug 2017
Accepted: 05 Feb 2018
Published online: 06 Aug 2018 *