Investigation on the Mechanical Properties of Powder Metallurgy-Manufactured AA7178/ZrSiO4 Nanocomposites

Srinivasan, Rajagopalan; Karunakaran, S.; Hariprabhu, M.; Arunbharathi, R.; Suresh, Sumathi; Nanthakumar, S.; Ahammad, S. K. Hasane; Mayakannan, S.; Jayakumar, Mani

doi:10.1155/2023/3085478

Cited by 2 publications

References 51 publications

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Fuzzy logic-driven genetic algorithm strategies for ultrasonic welding of heterogeneous metal sheets

Amale,

Singholi,

et al. 2024

AIP Advances

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There are a lot of problems with the conventional fusion welding process, so ultrasonic welding has been used for about 20 years and has helped a lot of manufacturing industries, including aviation, medicine, and microelectronics. Ultrasonic welding takes less than one second, making it suitable for mass production. Poor weld quality and joint strength are common issues that industries encounter as a result of this process. Actually, the success and quality of the welding are determined by its control parameters. This research examines the impacts of weld time, vibrational amplitude, and weld pressure on the welding of 0.6 mm thick sheets of two different metals, specifically copper and aluminum (AA2024). Responses, including tensile shear stress, weld area, and T-peel stress, are acquired through experiments that follow a full factorial design including four replicas. The highest recorded tensile shear stress was 4.34 MPa, the maximum weld area measured was 63.6 mm2, and the peak T-peel stress reached 1.22 MPa. A second-order non-linear regression model was constructed using all of these data points, which related the responses to the predictors. Due to the importance of quality in the production sector, the process parameters were determined by the combination of genetic algorithm (GA) and fuzzy logic (FL) approaches. The impact of the weld zone temperature on various quality characteristics has been investigated through experiments. It has been noted from the confirmatory test that FL produces superior output outcomes compared to the genetic algorithm, with FL achieving a fuzzy multi-performance index of 0.94 compared to 0.61 for GA. By conducting microstructural analysis, weld quality levels, including “under-weld,” “good weld,” and “over-weld,” were established.

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Fuzzy logic-driven genetic algorithm strategies for ultrasonic welding of heterogeneous metal sheets

Amale,

Singholi,

et al. 2024

AIP Advances

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Characterization of Graphene and Titanium Carbide Reinforced Magnesium Alloy Composite for Transmission Housings in Automobile

Senthilkumar

2024

SAE Technical Paper Series

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<div class="section abstract"><div class="htmlview paragraph">This study presents the mechanical characterization studies on 3 wt.% graphene (Gr) filled magnesium matrix composite reinforced with different weight fractions (4, 8, 12, 16, and 20 wt.%) of titanium carbide (TiC) particles. The matrix is AZ91 alloy, and the nano magnesium composite (NMC) is fabricated via a squeeze casting approach. The lightweight NMC is a potential solution for the automobile industry, as it reduces greenhouse gas emissions and contributes to environmental sustainability. Gr is added to enhance the composite's thermal endurance and mechanical strength. Mechanical and corrosion studies are performed as per the ASTM standards. The inclusion of Gr and 16 wt.% TiC tends to enhance the mechanical durability and corrosion resilience of the NMC when compared with other fabricated composites and cast alloys. The uniform dispersal of NC and TiC and better mould properties lead to better strength. Higher inclusion of TiC (20 wt.%) leads to brittleness, thereby decreasing the overall wear loss by resisting abrasive, which lowers the composite's flexibility and strength. The potential mechanism of adhesive wear is shown by the fact that TiC and Gr decrease the intimate contact region between the composite and the EN31 counter-disc. Compared with as-cast alloy, AZ91+3%Gr+16%TiC produced 64.31% higher porosity, 19.50%, 26.69%, 59.45%, and 19.66% higher UTS, micro-hardness, impact, and flexural strength.</div></div>

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Investigation on the Mechanical Properties of Powder Metallurgy-Manufactured AA7178/ZrSiO4 Nanocomposites

Cited by 2 publications

References 51 publications

Fuzzy logic-driven genetic algorithm strategies for ultrasonic welding of heterogeneous metal sheets

Fuzzy logic-driven genetic algorithm strategies for ultrasonic welding of heterogeneous metal sheets

Characterization of Graphene and Titanium Carbide Reinforced Magnesium Alloy Composite for Transmission Housings in Automobile

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