Abstract
This paper summarizes components and phases involved in the cupola melting process, then brings out a composition forecasting model based on the minimum Gibbs energy principle and the equilibria calculation algorithms of multiphase and multicomponent. Besides, the relationship between the melting parameters and the composition of molten iron is set up by using BP neural network based on the idea of indirect constraints. Finally, the paper probes the feasibility of the composition forecasting model with two examples. The application result shows that the prediction with this method can achieve strong practicability and popularization value.
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