Slag viscosity modeling toolbox

Abstract

Slag viscosity models are applied in many industries. However, the models are only applicable to a limited range of slag compositions and conditions, and their performance is not easily assessed. The present study describes tools that have been developed to assist slag viscosity model users in the selection of the best model for given slag compositions and conditions, and to help users determine how well the model will perform. The tools, which are in the form of several publicly available files and programs, include a slag viscosity prediction calculator with 24 slag viscosity models, and a database of 4124 slag viscosity measurements. The database includes over 750 compositions from 53 published studies. New slag viscosity models, integrated into the tools, include an artificial neural network for fully molten slags, and a viscosity prediction modifier for slags containing solid particles. Glass forming, entrained flow gasification and blast furnace case studies are provided to demonstrate how the slag viscosity modeling tools can be applied and to highlight certain features that should be considered when using slag viscosity models and experimental data.