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Ironmaking & Steelmaking
Processes, Products and Applications
Volume 46, 2019 - Issue 8
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Research Articles

Optimisation of the MgO/Al2O3 ratio of high-alumina BF slag based on MOPSO algorithm

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Pages 712-720 | Received 03 Jul 2017, Accepted 17 Oct 2017, Published online: 30 Nov 2017
 

ABSTRACT

To reduce the content of MgO in the slag, which helps in lowering production costs, the chemical components of a SiO2–CaO–MgO–Al2O3–TiO2 blast furnace (BF) slag system with high Al2O3 content were optimised using the multi-objective particle swarm optimisation (MOPSO) algorithm. First, models for predicting the metallurgical properties of BF slag were established and verified, based on mixture experimental designs and the ion and molecule coexistence theory. Second, the problem was solved by MOPSO using the MATLAB software package. Optimisation results show that the appropriate content of MgO in the slag should be 4–7%, and the MgO/Al2O3 ratio should be 0.2–0.6. Finally, optimised solutions were used in the 3200 m3 BF of a steel company in China. MgO in the slag was reduced to less than 5%, the MgO/Al2O3 ratio was controlled at 0.3–0.4, and the fuel ratio remained at 515 kg t−1.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The authors are grateful for the support from the National Science Foundation of China (No. 51574063) and Fundamental Research Funds for the Central Universities (N150204012).

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