Parametric optimization of removing iron from solid waste melts based on analysis of real-time coupled two-phase interface in an induction heating furnace

Henghua Lv, Lixia Kang, Kai Wang and Yongzhong Liu

Energy, 2022, vol. 261, issue PA

Abstract: The removal of iron oxide impurities in aluminosilicate solid wastes is crucial to realizing the high-value utilization of solid waste. In this work, a parametric optimization method for the separation process of iron-rich phase from solid wastes driven by electromagnetic was proposed. The induction heating model of two-phase melt in the iron removal process in an electromagnetic induction furnace was established, in which the real-time coupling of electromagnetic field, temperature field, velocity field, and the two-phase interface is realized by using the level set method. Based on this numerical model, the optimal configuration for the initial volume fraction of the metal phase, current intensity, and frequency of magnetic field on the formation process of the two-phase interface and flow and heat transfer in two-phase melt were investigated. The results showed that compared with the single-phase flow, the two-phase flow is more conducive to elevating the temperature of melts. When optimizing the operational parameters, the optimal range of the initial volume fraction of the metal phase should be determined first based on the principle of fewer circulations and higher velocity in the melt. The optimal range of the initial volume fraction of the metal phase is 3%–4% in the case of this work. Then, the optimal frequency of the magnetic field corresponding to the maximum velocity can be obtained, and the appropriate current intensity can be chosen to meet the requirement of smelting in the induction furnace. The proposed parametric optimization method provides theoretical fundamentals for the configuration of the design and operating parameters of the induction furnaces.

Keywords: Parametric optimization; Metal phase; Glass melt; Two-phase interface; Numerical simulation (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:261:y:2022:i:pa:s0360544222020850

DOI: 10.1016/j.energy.2022.125195

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