Water Absorption Behavior of Jute Fibers Reinforced HDPE. Biocomposites: Prediction Using RSM and ANN Modeling

The main objective of the present study was to investigate both the effect of incorporating Jute Fibers (JF) into the high density polyethylene (HDPE) matrix and to model the water uptake behavior of the biocomposites (HDPE/%JF) using the artificial neural network (ANN) model to predict the absorption ratio as a function of immersion time. Due to the fact that even partially biocomposites have a low resistance to moisture, which degrades their mechanical properties over time, their field of application is limited as a result of this notable defect. Absorption tests were carried out by immersing the biocomposite samples in distilled water at room temperature for several days until absorption became stable. Water absorption increased with both jute filler loading and immersion time and that the uptake process was fast at the begging of the experiments to reach saturation in time immersion close to 120 h. The results of ANN predicted values are close to the parity thresh- old; they are in perfect agreement with those obtained experimentally. Thus, the ANN method is able to reliably predict the water absorption of HDPE/% Jute fiber biocomposites. Therefore, it should be concluded that the ANN model provides better prediction accuracy than the RSM model. Finally, the findings of this study have positive implications for future applications of HDPE/%Jute biocomposites whether in the design or maintenance phase; application engineers can easily determine the swelling coefficient of such biocomposites without experimentation, saving thus money and time.