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Artificial Intelligence and Digitalization for Sustainable Development. 10th EAI International Conference, ICAST 2022, Bahir Dar, Ethiopia, November 4-6, 2022, Proceedings

Research Article

Process Parameter Optimization of Single Lap-Bolt Joint Date Palm Fiber Reinforced Polyester Composite Using ANN-Genetic Algorism

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  • @INPROCEEDINGS{10.1007/978-3-031-28725-1_3,
        author={Ermias Wubete Fenta and Assefa Asmare Tsegaw},
        title={Process Parameter Optimization of Single Lap-Bolt Joint Date Palm Fiber Reinforced Polyester Composite Using ANN-Genetic Algorism},
        proceedings={Artificial Intelligence and Digitalization for Sustainable Development. 10th EAI International Conference, ICAST 2022, Bahir Dar, Ethiopia, November 4-6, 2022, Proceedings},
        proceedings_a={ICAST},
        year={2023},
        month={3},
        keywords={DPFRPC Single lap Bolt joining ANN GA Tensile strength},
        doi={10.1007/978-3-031-28725-1_3}
    }
    
  • Ermias Wubete Fenta
    Assefa Asmare Tsegaw
    Year: 2023
    Process Parameter Optimization of Single Lap-Bolt Joint Date Palm Fiber Reinforced Polyester Composite Using ANN-Genetic Algorism
    ICAST
    Springer
    DOI: 10.1007/978-3-031-28725-1_3
Ermias Wubete Fenta,*, Assefa Asmare Tsegaw
    *Contact email: ermiw2010@gmail.com

    Abstract

    Natural fiber reinforced polymer composites are widely employed in automotive, aerospace, and civil applications due to their high strength-to-weight ratios and these applications require joining composite. Bolt joining of composite materials is the most prevalent way of joining, due to its efficiency of transferring load and ease of disassembly. However, bolt joining of composite is largely influenced by geometrical parameters such as edge to diameter ratio (E/D), width to diameter ratio (W/D), and fiber orientation. This work emphases on the process parameters optimization of single lap bolt joint date palm fiber reinforced polyester composite (DPFRPC) to improve the joint strength. The study was conducted experimentally by making single lap bolt joining of DPFRPC under tensile testing. The important factors affecting the performance of the adhesively joint such as E/D (1.5, 2.5, and 3.5), W/D (2.5, 3.5, and 4.5), and fiber orientation (0/0°, 45/−45°, and 0/90°) was studied using L9orthogonal array experimental design. Artificial neural network (ANN) was used to model the experimental results. Genetic algorithm (GA) optimization technique was used to determine the optimum process parameters. Using this technique, the optimum parameters of single lap bolt joint DPFRPC were, 3.5 E/D, 4.5 W/D, and 56.5° fiber orientation, with a load carrying capacity of 9.52 kN.

    Keywords
    DPFRPC Single lap Bolt joining ANN GA Tensile strength
    Published
    2023-03-19
    Appears in
    SpringerLink
    http://dx.doi.org/10.1007/978-3-031-28725-1_3
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