Laser powder bed fusion (LPBF), one of the most promising additive manufacturing (AM) techniques, has enabled the production of previously impossible structures. This breakthrough in AM has not only facilitated the creation of new designs, but also the redesign of existing industrial and engineering components to produce lightweight and highly efficient dies and molds, biomaterial scaffolds, aircraft brackets, heat sink and heat exchangers. In many of the mentioned applications in industries such as automotive, aerospace, heat exchanger, and electronics, aluminum (Al), Al alloys, and Al matrix composites (AMCs) are considered potential candidates.
In the first phase of this study, the optimum powder particle size and size distribution of an Al alloy powder (i.e., AlSi10Mg) was determined with the aim being to achieve highest densification levels and dimensional accuracies. In the second phase, three materials with high thermal conductivities were selected, namely, pure Al, AlSi12 and AlSi10Mg alloys. Since Al/Al alloys are prone to oxidation, the LPBF process parameters were optimized not only in terms of the densification level but also oxygen content of the fabricated parts. It was found out that the rate of oxide diminishment for Al/Al alloys during the LPBF process is more than in-situ oxidation. Despite the efforts, the optimized LPBF fabricated samples showed lower thermal conductivity than their conventionally manufactured counterparts. To tackle the issue, two different potential solutions were put into test. In the third phase, the influence of preheating on thermal properties of pure Al, AlSi12, and AlSi10Mg was investigated and a huge improvement in the thermal conductivity of the optimized as-built parts was obtained. In the fourth phase, the possibility of enhancing thermal conductivity of the LPBF fabricated Al/Al alloys in as-built condition through the incorporation of a second constituent with a higher thermal conductivity (i.e., graphene) was investigated. / Thesis / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/28615 |
| Date | January 2023 |
| Creators | Ghasemi, Ali |
| Contributors | Elbestawi, Mohamed, Mechanical Engineering |
| Source Sets | McMaster University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
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