Artificial neural network study of the electrical conductivity of mould flux

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.

Effect of pulsating solidification on the surface properties of conductive materials

“…Its surface is usually very rough. The molten oxide mixture is electric conductive (via the moving ionized atoms [ 10 ]) in liquid and semi-solid states, which provides an ideal case to validate the proposed theory on pulsating solidification. The experiments, including materials, methods and results, are reported in §2.…”