Abstract
The electrical conductivity of mould flux with chemical constitution of CaO-SiO2-Al2O3-NaO-K2O-MgO-CaF2-Cr2O3-FeO-MnO has been investigated. The assessed database contains one unitary, five binary, nine ternary, four quaternary, two quinary, two senary and one octonary subsystems. Each constitutional component is in connection to another via some direct or indirect links. A multilayer artificial neural network method was developed and implemented in the database. The work provides a method to calculate the relationships between the composition, temperature and electrical property of the mould flux within the defined parameter ranges. The results have been validated against those experimental data that are not included in the training of the neural networks.
Highlights
Many steelmaking companies are using a mould flux with chemical constitution of CaO-SiO2-Al2O3-NaOK2O-MgO-CaF2-Cr2O3-FeO-MnO to cast stainless steels in continuous casting mould
The work provides a method to calculate the relationships between the composition, temperature and electrical property of the mould flux within the defined parameter ranges
The primary driving force to study the electrical properties of mould powder is for electroslag remelting processing [3,4]
Summary
Many steelmaking companies are using a mould flux with chemical constitution of CaO-SiO2-Al2O3-NaOK2O-MgO-CaF2-Cr2O3-FeO-MnO to cast stainless steels in continuous casting mould. The work provides a method to calculate the relationships between the composition, temperature and electrical property of the mould flux within the defined parameter ranges. This work intends to provide a method to calculate the constitution and temperature-dependent electrical conductivity of the mould flux.
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