Modeling and Optimization of Tensile Properties of Epoxy Biocomposites Reinforced with Washingtonia robusta Waste and Biochar Using Response Surface Methodology, Artificial Neural Networks, and Multi-Criteria Decision-Making
The current study examined the tensile properties of epoxy biocomposites reinforced with untreated and NaOH-treated Washingtonia robusta waste (WRW) and biochar considering different fiber weight fractions (10%, 20%, 30%), NaOH concentrations (2%, 2.5%, 3%), and treatment durations (4, 12, 24 h). Th...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Journal of Natural Fibers |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/15440478.2025.2540475 |
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| Summary: | The current study examined the tensile properties of epoxy biocomposites reinforced with untreated and NaOH-treated Washingtonia robusta waste (WRW) and biochar considering different fiber weight fractions (10%, 20%, 30%), NaOH concentrations (2%, 2.5%, 3%), and treatment durations (4, 12, 24 h). The potential of WRW/biochar composites for sustainable applications, particularly in the automotive sector, was highlighted. The maximum tensile strength (35.69 MPa) and Young’s modulus (7.67 GPa) were achieved at 30% WRW treated for 4 h with 3% NaOH. These improvements are attributed to better interfacial bonding and fiber-matrix adhesion. To model and optimize the mechanical behavior, Response Surface Methodology (RSM), Artificial Neural Networks (ANN), and a Multi-Criteria Decision-Making (MCDM) method based on TOPSIS were applied. ANN provided higher predictive accuracy (R2 = 0.9993 for tensile strength, 0.9819 for Young’s modulus) compared to RSM. Optimization results indicated ideal conditions of 29.35–29.41% WRW, 11.06–11.24 h treatment time, and 2.99–3% NaOH, based on desirability function RSM and genetic algorithm ANN optimization. The integration of ANN, RSM, and TOPSIS-MCDM provided a comprehensive optimization framework, confirming the potential of WRW/biochar composites for eco-efficient engineering applications, such as in the automotive sector. |
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| ISSN: | 1544-0478 1544-046X |