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Abstract
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: This study employs friction stir processing to create a surface alloy using Al1050 aluminum
as the base material, with Cu powder applied to enhance surface properties. Various parameters,
including tool rotation speed, feed rate, and the number of passes, are investigated for their effects
on the microstructure and mechanical properties of the resulting surface alloy. The evaluation
methods include tensile testing, microhardness measurements, and metallographic examinations.
The initial friction stir alloying pass produced a non-uniform stir zone, which was subsequently
homogenized with additional passes. Through the plasticization of Al1050, initial agglomerates of
copper particles were compacted into larger ones and saturated with aluminum. The alloyed samples
exhibited up to an 80% increase in the strength of the base metal. This significant enhancement
is attributed to the Cu content and grain size refinement post-alloying. Additionally, machine
learning techniques, specifically Genetic Programming, were used to model the relationship between
processing parameters and the mechanical properties of the alloy, providing predictive insights for
optimizing the surface alloying process.
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