Steel Alloy Homogenization During Rheinsahl–Heraeus Vacuum Treatment: Conventional Computational Fluid Dynamics, Recurrence Computational Fluid Dynamics, and Plant Observations

Abstract

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.

Computational Fluid Dynamics–Discrete Phase Method Simulations in Process Engineering: A Review of Recent Progress

“…In industries, such as metallurgy, chemical engineering, and pharmaceuticals, CFD-DPM is used to track and control the product quality in multiphase flow [87,88]. By simulating the flow of metal and the movement of inclusions, the production process is monitored and controlled to improve the consistency and quality of the final product.…”

“…The integration of plant observations with simulation results is a strength, but the study may be limited by the specific conditions of the treatment process. Future work could involve broader applications and comparisons with other metallurgical processes [87]. Kou et al applied a coupled CFD-DPM approach to simulate multiphase flow in autoclaves [94].…”

Big Data Handling in Process Surveillance and Quality Control of Secondary Metallurgical Processes

“…The estimation of the efficiency of stirring and degree of homogenization is a current topic of interest in metallurgical research and simulation. [1][2][3] There are two main categories of treatments in RH plants: degassing and decarbonization. In degassing treatments, the focus lies on the removal of excess nitrogen and hydrogen from the steel, while the oxygen content at the start of the RH process is already quite low, having been tuned accordingly in the converter process.…”

On Modelling Parasitic Solidification Due to Heat Loss at Submerged Entry Nozzle Region of Continuous Casting Mold

“…To speed-up the coupled problem simulation, reduced order models have been continuously developed [23,65,66]. The recently proposed recurrence methodology (rCFD) reported in [67] uses collected statistics to extrapolate simulation results for the steady-state processes and (partially) the transient processes [68][69][70][71][72]. Efficient techniques to solve the linear system of equations for the CFD problems using graphical cards have become very popular [73].…”