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Titre: Exploring tensile properties of bio composites reinforced date palm fibers using experimental and Modelling Approaches
Auteur(s): Saada, Khalissa
Zaoui, Moussa
Amroune, Salah
Benyettou, Riyadh
Hechaichi, Amina
Jawaid, Mohammad
Hashem, Mohamed Ibrahim
Uddin, Imran
Mots-clés: ANN
Box-Behnken
Bio-composite
Mechanical properties
ANOVA
RSM
Date de publication: 2024
Editeur: Elsevier
Collection/Numéro: Materials Chemistry and Physics/ Vol. 314, Art. N° 128810(2024);pp. 1-13
Résumé: The objective of this study was to assess the tensile strength of epoxy bio-composites reinforced with palm fibers, both untreated and treated with sodium carbonate NaHCO3 at a concentration of 10 % (w/v) for 24 and 96 h, with varying weight percentages of fibers (15 %, 20 %, 25 %, and 30 %). To predict the mechanical performance of the composites, two methods were employed: artificial neural network (ANN) and response surface methodology (RSM). A Box-Behnken RSM design was used to conduct experiments and establish a mathematical model of the bio-composite behavior as a function of the fiber percentage in the samples, specimen cross-section, and treatment time. The ANN forecasts showed consistent expected values for the bio-composite sample behavior, with a correlation coefficient (R2) greater than 0.98 for Young's modulus and 0.97 for stress. Similarly, the correlation coefficients obtained by RSM for the mechanical properties were also highly satisfactory, with an R2 of 0.89 for Young's modulus and 0.87 for stress. Finally, the errors generated by each method (Box-Behnken and ANN) were compared to the experimental results.
URI/URL: https://doi.org/10.1016/j.matchemphys.2023.12881
https://www.sciencedirect.com/science/article/abs/pii/S0254058423015183?via%3Dihub
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/13877
ISSN: 0254-0584
Collection(s) :Publications Internationales

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