ABSTRACT
The main aim is to analyse the impact strength of coir-graphene composites reinforced with carbon fibre by varying the composition of graphene. The composites are prepared with 1%, 2%, 4% and 6% graphene by weight. The coir fibres are arranged in uniaxial direction. Moulds are made according to A-370 ASTM standard. Charpy impact test is conducted after the specimens are taken out of the moulds. Statistical analysis is done using two-way analysis of variance (ANOVA) having the parameters: percentage composition of graphene and type of mould. Neural networks are used for authentication of the test data. Artificial neural network (ANN) model is established between impact strength (input) and percentage composition of graphene (output). The high accuracy of the ANN model in this research proves the truthfulness of the data. FTIR (Fourier Transform Infrared Spectroscopy) analysis is further done on the composites for determining their chemical properties. Finally, Field Emission Scanning Electron Microscopy (FESEM) analysis is performed on specimens for examining the morphology of different constituents present inside the composites.
