Affiliations: Department of Advanced Design and Optimization, Central Mechanical Engineering Research Institute (CSIR-CMERI), MG Avenue, Durgapur, West Bengal, India | Kanpur Genetic Algorithms Laboratory (KanGAL), Department of Mechanical Engineering, Indian Institute of Technology, Kanpur, Uttar Pradesh, India | School of Materials Science and Engineering, Bengal Engineering and Science University, Shibpur, Howrah, West Bengal, India | Deparment of Engineering Design and Production, Foundry Engineering, Aalto University, Espoo, Finland
Note: [] Corresponding author. Arup Kumar Nandi, Department of Advanced Design and Optimization, Central Mechanical Engineering Research Institute (CSIR-CMERI), MG Avenue, Durgapur-713209, West Bengal, India. Tel.: +91 343 6452027; Fax: +91 343 2546745; E-mail: [email protected]
Abstract: Evaluation of equivalent thermal conductivity (ETC) of particle reinforced polymer composites (PRPCs) is a complex process since some of the influencing parameters are associated with uncertainties and ambiguities (e.g., dispersion state of filler in the matrix, uniformity of filler particle size and shape, etc). By realizing it, an attempt has been made to model the ETC of 2-phase PRPCs based on a genetic fuzzy approach. The model performance is rigorously tested in three stages to establish its practical applicability: based on experimental data (not used in model development) cited in literature, new measured thermal conductivities of flexible mould composites and finally by assessing the feasibility of values of missing data in the reported in-complete data set based on the developed model. Estimations of ETC by the proposed model are shown reasonable, even better compare to existing models and suggesting a generic model applicable to a wide range of 2-phase PRPCs.
