04/2022
10.3390/met12040656
Metals 2022
Aluminum, Castings, Foundry Technologies, Ibon Lizarralde, Jon Sertucha, Materiales ligeros, Mechanical properties, Prediction, Tecnologías inteligentes de fabricación
Aluminum-silicon-magnesium alloys are commonly used in the automotive industry to produce structural components. Among usual quality controls of produced castings, microstructure characterization and determination of mechanical properties are the most critical aspects. However, important problems can be found when measuring mechanical properties in those areas of castings with geometrical limitations. In this investigation, a set of A356 alloys have been prepared and then used to manufacture test castings and automotive castings in a laboratory and in industrial conditions, respectively, using Low Pressure Die Casting (LPDC) technology. Test castings were used to predict secondary dendritic arm spacing (SDAS) by using thermal parameters obtained from experimental cooling curves.
The results have been then compared to the ones found in the literature and improved methods for estimating SDAS from cooling curves have been developed. In a subsequent step, these methodologies have been checked with different industrial castings by using simulated cooling curves and experimentally measured SDAS values. Finally, the calculated SDAS values together with the Mg contents present in A356 alloys and the temperature and aging time data have been used to develop new models so as to predict the tensile properties in different areas of a given casting prototype. These developed models allow casters and designers predicting tensile properties in selected areas of a given prototype casting even during design and simulation steps and considering the processing variables expected in a given foundry plant. The structures of these new models have been described and experimentally validated using different processing conditions.
Al-Si-Mg alloys; mechanical properties; solidification parameters; SDAS; automotive castings; LPDC; prediction models.
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