Numerical Simulation of Solidification and Shrinkage Prediction of Cast Irons

研究将开发基于数值模拟的收缩预测标准，以优化商业球墨铸铁件和灰口铸铁件的铸造设计。最初的重点将放在球墨铸铁上。这种重要的商业合金的收缩预测不仅因为凝固行为的复杂性，而且由于其对冶金工艺条件的极端敏感性而变得复杂。因此，开发实用的设计软件的一个基本要求是开发一个能真实反映冶金工艺对凝固方式和顺序的影响的铸铁凝固动力学模型。将开发一种结合微观建模和热分析的方法来模拟凝固作用，以及根据能量和质量守恒和热力学考虑，将凝固模型应用于估算冻结过程中的体积变化的算法。这项研究的最终目标是开发一种基于计算机的综合方法，用于过程控制、铸件设计优化和铸件缺陷诊断，其中考虑了冶金变量、造型因素和几何形状对铸件质量的相互依赖的影响。由于经验是唯一可用的工具，所以在工业中，铸件的设计是通过一个涉及大量试验和错误的过程。该项目包括开发一种设计工具，该工具结合了当前对铸造金属冶金的理解和研究项目产生的其他见解。因此，可以更精确地设计零件，从而减少失败尝试的次数。

Research will develop numerical simulation-based shrinkage prediction criteria for the optimization of casting design of commercial ductile and gray iron castings. The initial focus will be on ductile iron. Shrinkage prediction for this important commercial alloy is complicated not only by the complexity of solidification behavior, but also by its extreme sensitivity to metallurgical processing conditions. Thus, an essential requirement for the development of practically useful design software is the development of a kinetic model of cast iron solidification which realistically accounts for the effects of metallurgical processing on mode and sequence of the solidification. A combined micro-modeling/thermal analysis approach to solificaction modeling will be developed, along with an algorithm for applying the solidifaction model to the estimation of volume changes during freezing on the basis of conservation of energy and mass, and thermodynamic considerations. The ultimate goal of the research is the development of an integrated computer-based methodology for process control, optimization of casting design, and diagnosis of casting defects which takes into account the interdependent effects of metallurgical variables, molding factors, and geometry on casting quality. Castings are designed in industry by a process that involves much trial and error, since experience is the only available tool. This project involves the development of a design tool which incorporates current understanding of the metallurgy of the cast metal and additional insights that result from the research project. Therefore, parts can be designed more precisely, reducing the number of failed attempts.