4.7 Article

Optimization of T5 heat treatment in high pressure die casting of Al-Si-Mg-Mn alloys by using an improved Kampmann-Wagner numerical (KWN) model

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ELSEVIER SCIENCE SA
DOI: 10.1016/j.msea.2023.144604

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Aluminum alloys; Die casting; Heat treatment; Mechanical properties; KWN model; Property map

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The increased use of lightweight aluminum die castings in the automotive industry has prompted the development of new die casting alloys and their heat treatment processes. This paper presents the development of an integrated precipitation and strengthening framework based on an improved Kampmann-Wagner numerical (KWN) model to predict the hardness and yield strength of high pressure die casting (HPDC) Al-11Si-xMg alloys during T5 aging process. The study shows that the increased Mg content enhances the hardness and yield strength due to the formation of Mg2Si phase and higher precipitate density of needle-like Mg5Si6-beta'' phase.
The increased use of lightweight aluminum die castings in the automotive industry leads to new die casting alloys and their heat treatment processes to meet performance requirements. In this paper, an integrated precipitation and strengthening framework based on an improved Kampmann-Wagner numerical (KWN) model was developed to predict the hardness and yield strength (YS) of high pressure die casting (HPDC) Al-11Si-xMg (x = 0.3 and 0.6) alloys during T5 aging (artificial aging after casting) process. The hardness and YS of the alloys were measured and compared with the predication results, for T5 treatment at 190 degrees C, 210 degrees C, 225 degrees C and 240 degrees C, respectively. The increased Mg content (from 0.3 to 0.6%) leads to the formation of Mg2Si phase during solid-ification, which effectively increases the hardness and YS in as-cast conditions. Also, the higher Mg content results in increased peak strengths because of higher precipitate density of needle-like Mg5Si6-beta '' phase. This improved KWN model showed a good accuracy with experimental results. Mechanical property maps were generated to guide the design and optimization of T5 process window for these two important die casting aluminum alloys.

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