【作者】 邢伟；

【导师】 赫冀成；

【作者基本信息】 东北大学 ， 材料加工工程， 2008， 硕士

【摘要】 金属凝固过程中,流体流动强烈地改变了熔体中浓度场和温度场的分布,进而影响微观形核、生长过程,从而对金属的组织和性能产生重要的影响。为了更好地阐明流动对枝晶生长过程的作用规律,本文开发了元胞自动机(CA)模型,模型中将流场下枝晶尖端生长模型与可描述流场下非对称枝晶生长轮廓的偏心生长模型相结合,模拟了Al-Si二元合金在流场下的枝晶生长规律。研究表明,流场下枝晶尖端生长动力学模型体现了枝晶在流场中逆流生长最快的机制。采用CA模型对固定在熔体壁面上的多晶生长形貌进行了模拟。分析表明,增大流动强度、减小形核密度和过冷度,能促进枝晶偏向于逆流方向生长,进而增大了枝晶生长方向与形核壁面垂直方向的夹角(偏斜角)。其中,流动强度、形核密度、过冷度为影响流场下枝晶生长的内在因素,在本研究的参数取值范围内,流动强度为主控参数。由模拟得到的枝晶生长偏斜角与流动速度、凝固速率的关系符合Okano实验关联式[29]的结果。在以上工作的基础上,开发出流场中游离晶粒的迁移和碰撞长大模型,实现了对单晶粒的生长、迁移,两个晶粒的碰撞合并,粘附壁面及继续生长过程的模拟,从而为存在流动条件下预测实际合金的凝固组织形貌奠定了基础。更多还原

【Abstract】 The fluid flow in the melt changes the temperature field and concentration field, further influences the nucleation and growth procedure and finally affects the solidification microstructures and properties of the casting metals during the solidification processes. In order to study the mechanics of the fluid flow affecting on the growth of the dendrites, a Cellular Automaton (CA) model, which includes the dendrite tip growth kinetics in the presence of fluid flow and the decentred growth algorithm describing the evolution of the growth envelope of the grains in the flow field, is developed and applied to predict the solidification morphologies of Al-Si binary alloy in the forced flow field.It shows that the dendrite tip velocity is larger in the upstream direction than that in the downstream direction, which is embedded in the algorithm of the dendrite tip growth kinetics. The solidification morphologies of the multi-grains which are nucleated at the mold surface are predicted by the above CA model. It can be seen that with the increase of the fluid flow intensity, with the decrease of the nucleation density and the decrease of the undercooling, the dendrites are inclined to grow towards the upstream direction and the deflection angle, which is the angle between the dendrite growth direction and the direction perpendicular to the nucleation surface, is increased. The fluid flow intensity, the nucleation density and the undercooling are regarded as the internal parameters effecting the dendrite growth in the forced flow field and the influences of the fluid flow intensity on the dendrite growth dominates the influences of the other two. The predicted relationships of the deflection angle versus the flow velocity and the solidification rate agrees with the empirical relations of Okano.Further, the CA model combining the algorithm of the growth, the transport, the impingement and sticking to the mold surface for the single cluster, which is formed by one or more grains, and the two clusters in the flow field is developed and applied to the evolution of the growth of the two nucleuses in the melt. This makes it possible for the present CA model to predict the microstructures and morphologies in the presence of fluid flow during the realistic solidification processes.更多还原