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

TL;DR

This paper develops a data-driven reduced order model to efficiently predict residence time distribution in an industrial continuous casting tundish, validated through experiments and simulations, enabling real-time process optimization.

Contribution

The study introduces a novel ROM approach that accurately predicts RTD in a tundish, reducing computational costs and facilitating real-time analysis compared to traditional full order models.

Findings

ROM accurately matches experimental RTD curves

Thermal buoyancy has negligible effect on flow in the tundish

ROM significantly reduces computational time for RTD prediction

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.