| About this Abstract |
| Meeting |
2024 TMS Annual Meeting & Exhibition
|
| Symposium
|
Aluminum Reduction Technology
|
| Presentation Title |
Predicting Electrolyte and Liquidus Temperatures of Aluminium Smelting Cells for Power Modulation Using Dynamic Model |
| Author(s) |
Choon-Jie Wong, Jie Bao, Maria Skyllas-Kazacos, Barry Welch, Jing Shi, Nadia Ahli, Amal Aljasmi, Mohamed Mahmoud, Mustafa Mustafa |
| On-Site Speaker (Planned) |
Choon-Jie Wong |
| Abstract Scope |
Effective monitoring and precise control of electrolyte and liquidus temperatures (which together gives superheat levels) are imperative for optimising the performance, extending the lifespan, and improving the current efficiency of aluminium smelter cells. During periods of intensive and frequent power modulation, where the power input to the cell is altered, maintaining a perfect mass and thermal equilibrium becomes increasingly challenging. As a result, both bath temperature and superheat will invariably fluctuate. This paper presents a study of a power modulation event, as well as encouraging results on the use of a comprehensive dynamic model, which integrates mass and thermal balances, for the continuous prediction of the bulk electrolyte and liquidus temperatures, ledge thickness, and the bath compositions. This paper is working towards addressing the absence of continuous thermal measurements suitable for real-time thermal monitoring and control, especially under complex conditions introduced by power modulation. |
| Proceedings Inclusion? |
Planned: Light Metals |
| Keywords |
Modeling and Simulation, Aluminum, |