PREDICTION OF COMPRESSION STRENGTH OF BAMBOO REINFORCED LOW-DENSITY POLYETHYLENE WASTE (LDPEw) COMPOSITES
Agha Inya Ndukwe, Solomon Umoh, Chimezie Ugwochi, Christian Ogbuji, Chinedu Ngolube, Ferdinand Aliegu, Lilian Izuegbu
Quarterly No. 3, 2022 pages 142-149
DOI:
keywords: composite, compression strength, carbonized bamboo, low-density polyethylene waste, artificial neural network, multiple regression, hardness
abstract In this work, the compression strength of bamboo reinforced low-density polyethylene waste (water sachet waste) composites was predicted. The composites were produced using the compression moulding technique with the following formulations: LDPEw, 5, 10, 15, and 20 wt.% filler. The hardness and compression strength of the examined composites were found to increase when the amount of filler was raised, with the formulation containing 20 wt.% filler having the highest hardness and compression strength values of 59.37 HV and 12.72 MPa, respectively. The control (LDPEw) gave the lowest values of hardness (41.57 HV) and compression strength (8.6 MPa). Multiple regression (MR) and artificial neural networks (ANN) were utilized to predict the experimental compression strength of the produced composites with the hardness and filler composition as independent variables. The mean squared error results indicated that when compared with the multiple regression forecasts, the artificial neural network predictions not only had smaller errors but were also closer to the experimental compression strength values. It is recommended that other methods of producing composites, such as the pulverization process with a 40% higher filler content than what was used in this work, should be studied to ascertain if they provide better composite materials.