| Title: | Characterizing the effects of SiC and ▫$Al_2O_3$▫ on the mechanical properties of Al6082 hybrid metal matrix composites: an experimental and neural network approach : an experimental and neural network approach |
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| Authors: | ID Masood, A. A. (Author)
ID Ali, A. (Author)
ID Madhu, P. (Author)
ID Yashas Gowda, T. G. (Author)
ID Jeevan, T. P. (Author)
ID Sharath, B. N. (Author) |
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| Files: |  APEM19-2_281-292.pdf (1,42 MB)
MD5: DF91C7A87ED923D09CC48DDF7AD84C80
 https://apem-journal.org/Archives/2024/Abstract-APEM19-2_281-292.html
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FS - Faculty of Mechanical Engineering
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| Abstract: | The use of advanced materials in the field of aerospace and automotive applications has led to use of metal matrix composites (MMC’s) due to their excellent mechanical properties. Aluminium metal matrix composite is one of the materials which can be strengthened by reinforcing it with hard ceramic particles. In the current work Al6082 matrix hybrid composites reinforced with silicon carbide (SiC) and aluminium oxide (Al2O3) was developed by using stir casting technique. The weight percentage of SiC was varied from 0 wt.% to 8 wt.% and keeping 3 wt.% Al2O3 constants. The tensile, hardness, density and impact tests were conducted, and the results obtained revealed that the addition of silicon carbide and Al2O3 particles in Al6082 enhances the mechanical properties of the prepared hybrid composites. The artificial neural network (ANN) model, which was trained using a dataset consisting of experimental results, has effectively captured the correlation between the weight percentage (wt.%) of silicon carbide (SiC) and the mechanical properties of the composite material. Through the examination of this model, valuable insights can be obtained regarding the distinct contributions of SiC to the mechanical properties of Al6082. |
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| Keywords: | aerospace and automotive industry, manufacturing, stir casting, metal matrix composites, MMC, aluminium metal matrix composite (Al2O3), Silicon carbide (SiC), mechanical properties, artificial neural network (ANN) |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 06.05.2024 |
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| Article acceptance date: | 13.07.2024 |
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| Publication date: | 29.08.2024 |
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| Publisher: | Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering |
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| Year of publishing: | 2024 |
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| Number of pages: | str. 281-292 |
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| Numbering: | Vol. 19, no. 2 |
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| PID: | 20.500.12556/DKUM-96870  |
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| UDC: | 658.5 |
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| ISSN on article: | 1854-6250 |
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| COBISS.SI-ID: | 266750467 |
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| DOI: | 10.14743/apem2024.2.507 |
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| Copyright: | Content from this work may be used under the terms of the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. |
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| Publication date in DKUM: | 30.01.2026 |
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| Views: | 150 |
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| Downloads: | 2 |
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| Metadata: |    |
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| Categories: | Misc.
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