Computational fluid dynamics (CFD) simulations of steel flow in an Rheinsahl–Heraeus (RH) process are realized by a discrete phase model (DPM) for the driving bubble plumes, a volume of fluid (VoF) method for the free surface in the vacuum chamber (VC), and a large eddy simulations (LES) model for the transport and mixing of steel alloys. CFD simulations are opposed to particle image velocimetry (PIV) analyses of flow pattern at the bath surface in the VC. While simple Reynolds averaged turbulence models fail to reproduce these plant observations, LES agrees fairly well. Furthermore, the steel recirculation rate is compared with empirical correlations from the literature, yielding good agreement with respect to the dependency of the recirculation rate on the gas injection rate. The absolute value of the recirculation rate increases by 15%, in case (realistic) eroded edges are considered instead of a (unrealistic) sharp‐edged geometry. Data‐assisted recurrence CFD (rCFD) is applied to accelerate conventional CFD. The rCFD simulations yield a computational speed‐up of four orders of magnitude, enabling real‐time LES at full grid resolution of three million cells. Titanium homogenization in the steel ladle is addressed by means of rCFD and compared with corresponding plant trials yielding good agreement.

中文翻译：

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Rheinsahl-Heraeus真空处理过程中的钢合金均质化：常规计算流体动力学，递归计算流体动力学和工厂观测

Rheinsahl-Heraeus（RH）过程中钢流的计算流体动力学（CFD）模拟是通过离散相模型（DPM）实现的，用于驱动气泡羽流，采用一定体积的流体（VoF）方法实现真空中的自由表面腔室（VC）和大型涡流模拟（LES）模型用于钢合金的运输和混合。CFD模拟与VC中熔池表面流动模式的粒子图像测速（PIV）分析相反。尽管简单的雷诺平均湍流模型无法重现这些植物观测数据，但LES对此表示同意。此外，将钢的再循环率与文献中的经验相关性进行了比较，在再循环率对气体注入率的依赖性方面取得了很好的一致性。再循环率的绝对值增加了15％，如果考虑使用（不切实际的）侵蚀边缘而不是（不切实际的）锐利边缘几何形状。数据辅助循环CFD（rCFD）用于加速常规CFD。rCFD仿真可将计算速度提高四个数量级，从而在三百万个单元的全网格分辨率下实现实时LES。钢包中的钛均质化通过rCFD解决，并与相应的工厂试验进行了比较，得出了很好的一致性。