The formation of oxide-related defects, including entrained oxide inclusions and oxide-induced gas/shrinkage porosity, during cavity fill and solidification has been inextricably linked to reduced mechanical properties in aluminum castings. Although the oxide formation and entrainment process can be easily understood, it remains difficult to accurately predict the location and severity of oxide-related defects in solidification products. To address the lack of predictive capability, the oxide entrainment number (OEN) model was developed and coupled to a three-dimensional, computational fluid dynamics software to accurately predict both the location and severity of oxide-related defects in aluminum castings. This first computationally efficient model for such application was validated on a geometrically complex aluminum casting where the predictive capability was confirmed via X-ray computed tomography (CT). Additionally, the OEN model can be used to aid in location-specific property prediction as tensile samples taken from the casting showed a reduction in mechanical properties in regions of high defect concentrations predicted by the OEN. The validation of the new OEN model provides a crucial link in an integrated computation materials engineering framework for design and manufacturing of high-quality cast components.

中文翻译：

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预测铝铸件中与氧化物有关的缺陷的新模型

在型腔填充和凝固过程中，氧化物相关缺陷的形成，包括夹带的氧化物夹杂物和氧化物引起的气孔/收缩孔隙，与铝铸件的机械性能降低密不可分。尽管氧化物的形成和夹带过程很容易理解，但要准确预测凝固产物中与氧化物相关的缺陷的位置和严重程度仍然很困难。为了解决预测能力不足的问题，开发了氧化物夹带数 (OEN) 模型并将其与三维计算流体动力学软件相结合，以准确预测铝铸件中氧化物相关缺陷的位置和严重程度。这种应用的第一个计算高效模型在几何复杂的铝铸件上得到验证，其中预测能力通过 X 射线计算机断层扫描 (CT) 得到证实。此外，OEN 模型可用于帮助特定位置的性能预测，因为从铸件中提取的拉伸样品显示，在 OEN 预测的高缺陷浓度区域中，机械性能会降低。新 OEN 模型的验证为设计和制造高质量铸件的集成计算材料工程框架提供了一个关键环节。OEN 模型可用于帮助特定位置的性能预测，因为从铸件中提取的拉伸样品显示 OEN 预测的高缺陷浓度区域的机械性能降低。新 OEN 模型的验证为设计和制造高质量铸件的集成计算材料工程框架提供了一个关键环节。OEN 模型可用于帮助特定位置的性能预测，因为从铸件中提取的拉伸样品显示 OEN 预测的高缺陷浓度区域的机械性能降低。新 OEN 模型的验证为设计和制造高质量铸件的集成计算材料工程框架提供了一个关键环节。