Data-driven reduced order model for residence time distribution analysis of an industrial-scale continuous casting tundish

TL;DR

The paper tackles the challenge of efficiently predicting residence time distributions (RTD) in an industrial-scale single-strand tundish, a key determinant of steel cleanliness. It develops a non-intrusive, data-driven reduced-order model (ROM) based on proper orthogonal decomposition (POD) of high-fidelity CFD snapshots and radial basis function (RBF) interpolation to map time and operating parameters to reduced coefficients, enabling real-time RTD predictions. The full-order model (FOM) employs 3D Reynolds-averaged Navier–Stokes simulations with a $k$-$\varepsilon$ turbulence model and transient tracer transport under both isothermal and non-isothermal conditions (via the Boussinesq approximation) and is validated against experimental RTD data. Results show excellent agreement between ROM, FOM, and experiments, with the ROM achieving about $10^6$-fold speedups, demonstrating its potential for real-time monitoring, design optimization, and digital-twin applications in metallurgical processing.

Abstract

The continuous casting tundish plays a critical role as a metallurgical reactor in the continuous casting process, with its flow characteristics serving as a key parameter in the production of high-quality steel. These characteristics are typically assessed through residence time distribution (RTD) curves. This study examines the flow behaviour in a single-strand continuous casting tundish through a combination of numerical simulations and experimental validation. Steady-state full order model (FOM) simulations are performed under both isothermal and non-isothermal conditions to evaluate the influence of thermal buoyancy on the velocity field, which is found to be negligible. The resulting flow fields are used to initialize transient tracer transport simulations for determining the RTD and flow volume partitioning. Subsequently, a data-driven reduced order model (ROM) is developed to predict the RTD response. Comparison of RTD curves obtained from experiments, FOM, and ROM shows excellent agreement, with the ROM accurately capturing the key flow characteristics at a fraction of the computational cost. These results highlight the potential of ROM techniques for efficient real-time analysis, design, and optimization of tundish operations in metallurgical processes.

Figures (14)

• Figure 1: Schematic of a single-strand tundish (taken from Wang2021), illustrating key components and flow features. The diagram depicts multiphase interactions involving molten steel, slag, and inclusion flotation. Flow control devices, such as the impact pad (turbulence inhibitor) and dam, are also shown, highlighting their role in enhancing steel quality and casting performance.
• Figure 2: Isometric view of the computational domain for the 1:1 scaled single-strand tundish. The inlet and outlet locations are indicated; all remaining boundaries are considered as no-slip walls.
• Figure 3: Discretized computational domain of a 1:1 scaled single-strand tundish. Left: Isometric view of the mesh; Right: 2D midplane slice showing mesh refinement near the inlet jet impingement region and outlet, and with six prism layers adjacent to the walls.
• Figure 4: Time-dependent tracer concentration profile imposed at the inlet for the transient species transport simulation.
• Figure 5: Positions of the horizontal and vertical lines along which streamwise velocity profiles are extracted within the tundish.