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Title: Modelling of the effects of entrainment defects on mechanical properties in Al-Si-Mg alloy castings
Author: Yue, Yang
ISNI:       0000 0004 5363 5480
Awarding Body: University of Birmingham
Current Institution: University of Birmingham
Date of Award: 2014
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Entrainment defects such as double oxide films and entrapped bubbles occur frequently in aluminium alloy castings during the mould-filling process, and are very detrimental to both mechanical properties and reproducibility of casting properties. However, the behaviour of entrainment defects in the liquid metal and their evolution during the casting process are still unclear, and the distribution of these defects in casting remains difficult to predict. An algorithm, named the oxide film entrainment model (OFEM), that has the potential to predict the formation and distribution of entrainment defects in castings was studied and tried to validate using A356 alloy. The initial validation of OFEM used previous reported experimental data on mechanical properties of castings. Then modelling of three common entrainment mechanisms in fluid flow were conducted, and the predicted defects quantities in the samples were compared with the bending strengths of the castings. A further validation compared the tensile strength of the cast test bars with either the predicted number of defects, or the defect concentration within the bars obtained from the simulation. A general relationship between the mechanical strength of the cast test bars and the quantity of estimated defects was apparent. This research also assessed the behaviour of entrainment defects in the liquid state and during solidification using ultra-fast synchrotron X-ray radiography. The reconstructed images showed the 3D morphologies of entrainment defects and revealed the morphological evolution of the defects. Currently, the OFEM algorithm has not yet been fully validated. However, modelling work highlighted the potential of the method as an indicator for the entrainment severity in different mould designs. The effects of different modelling conditions on the modelling results were discussed, and some useful courses were suggested to achieve higher accuracy of model.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: TN Mining engineering. Metallurgy