Mixing Time Prediction in a Ladle Furnace

Author:

Guo Xipeng1,Liu Yun2,Jojo-Cunningham Yasmeen2,Silaen Armin1ORCID,Walla Nicholas1,Zhou Chenn1

Affiliation:

1. Center for Innovation through Visualization and Simulation (CIVS), Purdue University Northwest, Hammond, IN 46323, USA

2. Department of Mechanical and Civil Engineering, Purdue University Northwest, Hammond, IN 46323, USA

Abstract

This paper presents a study on the effectiveness of two turbulence models, the large eddy simulation (LES) model and the k-ε turbulence model, in predicting mixing time within a ladle furnace using the computational fluid dynamics (CFD) technique. The CFD model was developed based on a downscaled water ladle from an industrial ladle. Corresponding experiments were conducted to provide insights into the flow field, which were used for the validation of CFD simulations. The correlation between the flow structure and turbulence kinetic energy in relation to mixing time was investigated. Flow field results indicated that both turbulence models aligned well with time-averaged velocity data from the experiments. However, the LES model not only offered a closer match in magnitude but also provided a more detailed representation of turbulence eddies. With respect to predicting mixing time, increased flow rates resulted in extended mixing times in both turbulence models. However, the LES model consistently projected longer mixing times due to its capability to capture a more intricate distribution of turbulence eddies.

Funder

National Science Foundation

MRI program

GOALI program

Publisher

MDPI AG

Reference39 articles.

1. Mishra, B. (1998). Metals Handbook Desk Edition, ASM International.

2. Introducing the Planar Laser-Induced Fluorescence Technique (PLIF) to Measure Mixing Time in Gas-Stirred Ladles;Conejo;Met. Mater. Trans. B,2019

3. Effect of the Fluid-Dynamic Structure on the Mixing Time of a Ladle Furnace;Zenit;Steel Res. Int.,2017

4. Fluid flow, dissolution, and mixing phenomena in argon-stirred steel ladles;Duan;Metall. Mater. Trans. B,2018

5. Effect of Gas Blown Modes on Mixing Phenomena in a Bottom Stirring Ladle with Dual Plugs;Haiyan;ISIJ Int.,2016

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