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Title | Multi-performance optimization of the mechanical characteristics of basalt fiber and silicon carbide-filled aluminum matrix composites |
Authors |
Veeranaath, V.
Dinesh, S.G. Natarajan, G. |
ORCID | |
Keywords |
hybrid composites stir casting mechanical characterization grey relational analysis |
Type | Article |
Date of Issue | 2024 |
URI | https://devessuir.sumdu.edu.ua/handle/123456789/96469 |
Publisher | Sumy State University |
License | Creative Commons Attribution - NonCommercial 4.0 International |
Citation | Veeranaath V., Dinesh S. G., Natarajan G. (2024). Multi-performance optimization of the mechanical characteristics of basalt fiber and silicon carbide-filled aluminum matrix composites. Journal of Engineering Sciences (Ukraine), Vol. 11(2), pp. C1–C12. https://doi.org/10.21272/jes.2024.11(2).c1 |
Abstract |
In the existing state, aluminum metal matrix composites (AlMMCs) are a category of materials that have
successfully fulfilled the majority of demanding requirements in applications where moderate strength, high stiffness,
and lightweight are necessary. This paper is focused on processing aluminum hybrid composites by reinforcing the
aluminum alloy with a novel combination of fillers: basalt fibers and silicon carbide via stir casting. The main aim is
to study the impact of processing conditions on the properties of the developed composite. Nine samples are produced
by varying the reinforcement content, stirring rate, and duration based on the L9 Taguchi Array. SEM analysis is
utilized to examine the microstructure of the developed composites. The samples were also machined and tested for
their mechanical, physical, and wear behavior as per ASTM standards. The maximum density and hardness of
2883.3 kg/m3
and 45.6 HRB, respectively, are observed at higher filler content conditions. In contrast, the minimum
specific wear rate, maximum ultimate tensile, and impact strength of 1.86·10–5 mm3
/(N·m), 263.5 MPa, and 93 N/mm
are observed in higher stirring duration conditions. So, to avoid conflicting combinations of optimal input factors, grey
relational analysis (GRA) tied with principle component analysis (PCA) is employed to determine the multi-objective
performance parameter and the optimal combination of input factors for better response. Confirmatory tests were also
performed to verify and validate the same. ANOVA analysis is also utilized to assess the significance of the process
parameters on the responses. |
Appears in Collections: |
Journal of Engineering Sciences / Журнал інженерних наук |
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Veeranaath_jes_2_2024.pdf | 1.28 MB | Adobe PDF | 1 |
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