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<p>The collaborative recycling of spent refractory material (SRM) in the aluminum electrolytic cell is a promising method. Due to the multivariable, nonlinear, and strongly coupled nature of the electrolysis process parameters, their influence mechanisms on the dissolution behavior of SRM and alumina mixtures have not yet been fully elucidated. This study combined computational fluid dynamics-discrete element method (CFD-DEM) simulations with response surface methodology (RSM) to predict and optimize the dissolution process of the mixture. The effects of electrolyte temperature, mixture temperature, alumina concentration, silica concentration, and current density on the dissolution rate of the mixture, as well as the stability and uniformity of alumina and silica concentrations, were investigated. The results indicate that decreasing alumina and silica concentrations and increasing electrolyte temperature promote rapid dissolution of the mixture, while increasing alumina and silica concentrations enhance their stability and uniformity. The optimal parameters for controlling the electrolysis process are: electrolyte temperature of 960&#xa0;°C, mixture temperature of 300&#xa0;°C, alumina concentration of 2.952&#xa0;wt.%, silica concentration of 1.448&#xa0;wt.%, and current density of 0.75&#xa0;A/cm<sup>2</sup>. This research integrates CFD simulations with RSM optimization, thereby pioneering a novel pathway for the collaborative optimization and efficient design of process parameters in the aluminum reduction cell.</p> Graphical Abstract <p></p>

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Investigation and Multi-objective Optimization of Spent Refractory Material Particle Dissolution Using CFD-DEM and Response Surface Methodology

  • 期刊论文

  • 发表日期：

    2026年1月30日

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  • Xia Hu,
  • Wenyuan Hou,
  • Wei Liu,
  • Hantao Liu,
  • Hesong Li,
  • Xingguo Wei

摘要

The collaborative recycling of spent refractory material (SRM) in the aluminum electrolytic cell is a promising method. Due to the multivariable, nonlinear, and strongly coupled nature of the electrolysis process parameters, their influence mechanisms on the dissolution behavior of SRM and alumina mixtures have not yet been fully elucidated. This study combined computational fluid dynamics-discrete element method (CFD-DEM) simulations with response surface methodology (RSM) to predict and optimize the dissolution process of the mixture. The effects of electrolyte temperature, mixture temperature, alumina concentration, silica concentration, and current density on the dissolution rate of the mixture, as well as the stability and uniformity of alumina and silica concentrations, were investigated. The results indicate that decreasing alumina and silica concentrations and increasing electrolyte temperature promote rapid dissolution of the mixture, while increasing alumina and silica concentrations enhance their stability and uniformity. The optimal parameters for controlling the electrolysis process are: electrolyte temperature of 960 °C, mixture temperature of 300 °C, alumina concentration of 2.952 wt.%, silica concentration of 1.448 wt.%, and current density of 0.75 A/cm2. This research integrates CFD simulations with RSM optimization, thereby pioneering a novel pathway for the collaborative optimization and efficient design of process parameters in the aluminum reduction cell.

Graphical Abstract