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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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