Modeling Moisture Absorption of Flax/Sisal Reinforced Hybrid Biocomposites Using Fick’s and ANN Methods
Natural fiber composites are being increasingly used in several fields, owing to their considerable cost, weight, and environmental benefits. The objective of this research is to study the effect of water absorption on the behavior of laminated biocomposites using flax (F) and sisal (S) fiber biocom...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2023-04-01
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| Series: | Journal of Natural Fibers |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/15440478.2022.2140322 |
| Summary: | Natural fiber composites are being increasingly used in several fields, owing to their considerable cost, weight, and environmental benefits. The objective of this research is to study the effect of water absorption on the behavior of laminated biocomposites using flax (F) and sisal (S) fiber biocomposites with different stacking sequences (3S and 3F) and fiber orientation at 90° (F090s and S090s), as well as hybridizations (F/4S90/F and S/4F90/S) to reinforce an epoxy matrix. The kinetics of water diffusion within the proposed biocomposites was monitored and analyzed through a model-based optimization approach using artificial neural network (ANN) method. The results of this study showed that the amount of water absorbed by different types of biocomposites increased with time according to Fick’s law. Non-hybrid flax and sisal fiber composites (UD and (0/90°)s oriented) had lower water absorption rates than the hybrid orientation. It was also observed that sisal fiber was most sensitive to water absorption than flax. A high correlation of experimental data with the model was revealed which denoted that the ANN learning process was perfectly performed. Therefore, it was inferred that the ANN approach can accurately predict biocomposites water absorption. |
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| ISSN: | 1544-0478 1544-046X |