Mostafazade Abolmaali Ali, Bayat Mohamad, Nadimpalli Venkata Karthik, Dahmen Thomas, Hattel Jesper
Department of Civil and Mechanical Engineering, Technical University of Denmark, 2800 Kongens Lyngby, Denmark.
Materials (Basel). 2025 Sep 20;18(18):4392. doi: 10.3390/ma18184392.
This study aims to use Computational Fluid Dynamics (CFD) analysis to improve inclusion removal efficiency in tundishes used in the steelmaking industry, with the broader goal of promoting more sustainable steel production and supporting circular economy objectives by producing cleaner steel. Inclusions are non-metallic particles, such as alumina, that enter the tundish with the molten steel and travel through it; if not removed, they can exit through the nozzles and adversely affect the mechanical properties of the final product and process yield. An existing tundish design is modified using three passive techniques, including adding a vertical dam, adding a horizontal baffle, and inclining the side walls, to assess their influence on fluid flow behavior and inclusion removal. Residence time distribution (RTD) analysis is employed to evaluate flow characteristics via key metrics such as dead zone and plug flow volume fractions, as well as plug-to-dead and plug-to-mixed flow ratios. In parallel, a discrete phase model (DPM) analysis is conducted to track inclusion trajectories for particles ranging from 5 to 80 μm. Results show that temperature gradients due to heat losses significantly influence flow patterns via buoyancy-driven circulation, changing RTD characteristics. Among the tested modifications, inclining the side walls proves most effective, achieving average inclusion removal improvements of 8% (Case B1) and 19% (Case B2), albeit with increased heat loss due to greater top surface exposure. Vertical dam and horizontal baffle, despite showing favorable RTD metrics, generally reduce the inclusion removal rate, highlighting a disconnect between RTD-based predictions and DPM-based outcomes. These findings demonstrate the limitations of relying solely on RTD metrics for evaluating tundish performance and suggest that DPM analysis is essential for a more accurate assessment of inclusion removal capability.
本研究旨在利用计算流体动力学（CFD）分析来提高炼钢行业中间包的夹杂物去除效率，其更广泛的目标是通过生产更清洁的钢来促进更可持续的钢铁生产并支持循环经济目标。夹杂物是诸如氧化铝之类的非金属颗粒，它们随钢水进入中间包并在其中流动；如果不被去除，它们会通过水口流出，对最终产品的机械性能和工艺产量产生不利影响。采用三种被动技术对现有的中间包设计进行修改，包括添加垂直坝、添加水平挡板和倾斜侧壁，以评估它们对流体流动行为和夹杂物去除的影响。采用停留时间分布（RTD）分析通过关键指标（如死区和活塞流体积分数，以及活塞流与死区和活塞流与混合流的比率）来评估流动特性。同时，进行离散相模型（DPM）分析以跟踪粒径范围为5至80μm的颗粒的夹杂物轨迹。结果表明，由于热损失导致的温度梯度通过浮力驱动的循环显著影响流动模式，改变了RTD特性。在所测试的修改中，倾斜侧壁被证明是最有效的，平均夹杂物去除率提高了8%（案例B1）和19%（案例B2），尽管由于顶面暴露增加导致热损失增加。垂直坝和水平挡板尽管显示出良好的RTD指标，但通常会降低夹杂物去除率，这突出了基于RTD的预测与基于DPM的结果之间的脱节。这些发现证明了仅依靠RTD指标评估中间包性能的局限性，并表明DPM分析对于更准确地评估夹杂物去除能力至关重要。
