Dynamic Model for Metal Cleanness Evaluation by Melting in a Cold Crucible
Dynamic Model for Metal Cleanness Evaluation by Melting in a Cold Crucible
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通过在冷坩埚中熔化评估金属清洁度的动态模型
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
R. Brooks
中科院分区：
文献类型：
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作者：
V. Bojarevics;K. Pericleous;R. Brooks
在冷熔炉中熔化金属样品，由于表层电磁力的作用，导致夹杂物集中在表面。这个过程是动态的，包括熔化阶段，然后是准静态的颗粒分离，最后是在冷坩埚中的凝固。所提出的建模技术是基于耦合湍流流动、热场和电磁场的拟谱方法，在自由表面所包含的时变流体体积内，以及部分固体坩埚壁面内。该模型使用两种方法进行粒子跟踪：(1)直接拉格朗日粒子路径计算；(2)漂移浓度模型。实现了对任意非定常流动的拉格朗日跟踪。在拉格朗日模型中使用允许相对较大的时间步长的隐式推进来实现特定的数值时间积分方案。漂移浓度模型基于局部平衡漂移速度假设。对这两种方法进行了比较和论证，在定常流动情况下给出了定性相似的结果。给出了铁合金的具体结果。1μm量级的小颗粒不太容易被电磁场作用分离。相比之下，较大的颗粒，10到100μm，很容易被电磁场捕获，并根据它们的大小和性质停留在样品表面的预定位置。该模型允许对熔化功率、几何形状和凝固速度进行优化。
Melting of metallic samples in a cold crucible causes inclusions to concentrate on the surface owing to the action of the electromagnetic force in the skin layer. This process is dynamic, involving the melting stage, then quasi-stationary particle separation, and finally the solidification in the cold crucible. The proposed modeling technique is based on the pseudospectral solution method for coupled turbulent fluid flow, thermal and electromagnetic fields within the time varying fluid volume contained by the free surface, and partially the solid crucible wall. The model uses two methods for particle tracking: (1) a direct Lagrangian particle path computation and (2) a drifting concentration model. Lagrangian tracking is implemented for arbitrary unsteady flow. A specific numerical time integration scheme is implemented using implicit advancement that permits relatively large time-steps in the Lagrangian model. The drifting concentration model is based on a local equilibrium drift velocity assumption. Both methods are compared and demonstrated to give qualitatively similar results for stationary flow situations. The particular results presented are obtained for iron alloys. Small size particles of the order of 1 μm are shown to be less prone to separation by electromagnetic field action. In contrast, larger particles, 10 to 100 μm, are easily “trapped” by the electromagnetic field and stay on the sample surface at predetermined locations depending on their size and properties. The model allows optimization for melting power, geometry, and solidification rate.