Simulation of Ferrochrome Settling Behavior in a Submerged Arc Furnace Using a Multiphysics and Multiphase Model

Yu, Yang; Li, Baokuan; Liu, Zhongqiu; Qi, Fengsheng; Liu, Chengjun; Rong, Wenjie; Kuang, Shibo

doi:10.1007/s11663-023-02817-1

Cited by 4 publications

(1 citation statement)

References 27 publications

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“…For instance, Reference 1 delves into optimizing raw materials with high Al 2 O 3 content and enhancing processes in the SAF for increased aluminium and silicon extraction. In Reference 2 , a 3D transient mathematical model is presented to simulate multiphase flow and thermochemical reactions within an industrial furnace. Reference 3 applies computational fluid dynamics (CFD) and a 3D model to assess the operations of a SAF in ferronickel production.…”

Section: Introductionmentioning

confidence: 99%

Data-driven assisted real-time optimal control strategy of submerged arc furnace via intelligent energy terminals considering large-scale renewable energy utilization

Zheng,

Pan,

Liu

et al. 2024

Sci Rep

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This study presents a data-driven assisted real-time optimization model which is an innovative approach to address the challenges posed by integrating Submerged Arc Furnace (SAF) systems with renewable energy sources, specifically photovoltaic (PV) and wind power, with modern intelligent energy terminals. Specifically, the proposed method is divided into two stages. The first stage is related to data-driven prediction for addressing local time-varying renewable energy and electricity market prices with predicted information, and the second stage uses an optimization model for real-time SAF dispatch. Connections between intelligent energy terminals, demand-side devices, and load management systems are established to enhance local renewable resource utilization. Additionally, mathematical formulations of the operating resistance in SAF are explored, and deep neuron networks are employed and modified for dynamic uncertainty prediction. The proposed approach is validated through a case study involving an intelligent energy terminal with a 12.5 MVA SAF system and 12 MW capacity renewable generators in an electricity market with fluctuating prices. The findings of this research underscore the efficacy of the proposed optimization model in reducing operational costs and enhancing the utilization of localized renewable energy generation. By integrating four distinct dissatisfaction coefficients into the optimization framework, we demonstrate the model's adaptability and efficiency. The application of the optimization strategy delineated herein results in the SAF system's profitability oscillating between $111 and $416 across various time intervals, contingent upon the coefficient settings. Remarkably, an aggregate daily loss recovery amounting to $1,906.84 can be realized during the optimization period. Such outcomes not only signify considerable economic advantages but also contribute to grid stability and the diminution of renewable energy curtailment, thereby underscoring the dual benefits of economic efficiency and sustainability in energy management practices.

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Section: Introductionmentioning

confidence: 99%

Data-driven assisted real-time optimal control strategy of submerged arc furnace via intelligent energy terminals considering large-scale renewable energy utilization

Zheng,

Pan,

Liu

et al. 2024

Sci Rep

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Effective utilization of Ni-Cr bearing composite burdens for high-Cr ferronickel preparation

Xue,

Zhu,

Pan

et al. 2024

Powder Technology

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Numerical simulation study of the effect of nonlinear side blowing on the flow of gas-liquid two-phase flow

Su,

Wang,

Wang

et al. 2024

International Journal of Chemical Reactor Engineering

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The hydrodynamic and stirring characteristics of gas-slag-copper matte three-phase in side-blowing melt pool melting were numerically simulated using a combination of the volume of fluid (VOF) model in computational fluid dynamics and the realizable k-ε turbulence model. The study obtained macroscopic flow and gas-liquid two-phase distribution information of the flow field in the melting process. It also examined the effects of isokinetic blowing and nonlinear blowing on the fluid velocity, penetration depth, gas content, and turbulent eddy volume of the flow field, and compared the results. The results indicate that, for the same total gas volume, constant velocity blowing (CVS) inadequately agitates the molten pool, resulting in a large stirring dead zone within the flow field. In contrast, nonlinear blowing enhances the fluid velocity overall. Specifically, sinusoidal variable speed blowing (SWS) and rectangular variable speed blowing (RWS) reduce the stirring dead zone area by 79  and 73.5 %, respectively. This is attributed to the increase in maximum penetration depth and slag phase gas content, as well as the decrease in gas escape during nonlinear blowing. The vortex volume over the total calculated time for the three conditions is enhanced by 6.7  and 1.1 % for SWS and RWS, respectively. Additionally, the turbulent kinetic energy of the fluids is increased by 18.7  and 17 %, respectively.

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Simulation of Ferrochrome Settling Behavior in a Submerged Arc Furnace Using a Multiphysics and Multiphase Model

Cited by 4 publications

References 27 publications

Data-driven assisted real-time optimal control strategy of submerged arc furnace via intelligent energy terminals considering large-scale renewable energy utilization

Data-driven assisted real-time optimal control strategy of submerged arc furnace via intelligent energy terminals considering large-scale renewable energy utilization

Effective utilization of Ni-Cr bearing composite burdens for high-Cr ferronickel preparation

Numerical simulation study of the effect of nonlinear side blowing on the flow of gas-liquid two-phase flow

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