Ann Approach Based Study to Predict the Mechanical Properties of Copper Powder Filled Lldpe Composites

The effective mechanical properties of copper powder filled with linear low-density polyethylene (LLDPE) are studied by using artificial neural network (ANN) approach.It is a form of artificial intelligence, which deal with the function of human brain and nervous system.ANN technique is more important in many fields of engineering and research applications.This report presents the use of ANN technique for the accurate prediction of mechanical properties of copper powder filled LLDPE composites.ANN is based on Feed Forward Back Propagation (FFBP) using three different training functions (TRAINGDA, TRAINGDM, and TRAINGDX).The input parameters manipulated for prediction are Elongation at break, Stress at break, Young's modulus, volume fraction of the filler and many types of K constants.Copper filled with LLDPE have complex structure which is difficult to predict mechanical properties accurately.This prediction is done using ANN approach.Theoretical model is being compared with experimental data and found that comparison is in good agreement.