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Numerical Simulation and Optimization of Directional Solidification Process of Single Crystal Superalloy Casting

机译:单晶高温合金铸件定向凝固过程的数值模拟与优化

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The rapid development of numerical modeling techniques has led to more accurate results in modeling metal solidification processes. In this study, the cellular automaton-finite difference (CA-FD) method was used to simulate the directional solidification (DS) process of single crystal (SX) superalloy blade samples. Experiments were carried out to validate the simulation results. Meanwhile, an intelligent model based on fuzzy control theory was built to optimize the complicate DS process. Several key parameters, such as mushy zone width and temperature difference at the cast-mold interface, were recognized as the input variables. The input variables were functioned with the multivariable fuzzy rule to get the output adjustment of withdrawal rate (v) (a key technological parameter). The multivariable fuzzy rule was built, based on the structure feature of casting, such as the relationship between section area, and the delay time of the temperature change response by changing v, and the professional experience of the operator as well. Then, the fuzzy controlling model coupled with CA-FD method could be used to optimize v in real-time during the manufacturing process. The optimized process was proven to be more flexible and adaptive for a steady and stray-grain free DS process.
机译:数值建模技术的快速发展已导致对金属凝固过程进行建模的结果更加准确。在这项研究中,使用元胞自动机有限差分法(CA-FD)来模拟单晶(SX)高温合金叶片样品的定向凝固(DS)过程。进行实验以验证仿真结果。同时,建立了基于模糊控制理论的智能模型,以优化复杂的DS过程。几个关键参数,例如铸模界面的糊状区域宽度和温差,被认为是输入变量。将输入变量与多元模糊规则一起使用,以对退出率(v)(一项关键技术参数)进行输出调整。基于铸件的结构特征,如断面面积与通过改变v引起的温度变化响应的延迟时间之间的关系,以及操作人员的专业经验,建立了多变量模糊规则。然后,结合CA-FD方法的模糊控制模型可用于在制造过程中实时优化v。事实证明,经过优化的过程对于稳定且无杂散的DS过程具有更大的灵活性和适应性。

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