PNNL

Abstract

The activation energy of glass melt viscosity is nearly constant at temperatures at which viscosity is less than 100 Pa s. Provided that the preexponential factor is a composition-independent constant and, thus, only the activation energy is a function of composition, viscosity-composition relationships of utmost simplicity can be formulated. Such relationships provide a welcome advantage in computational fluid dynamics modeling of glass melting furnaces, especially those processing highly multicomponent glasses. Using a dataset with over 3 thousand viscosity values acquired experimentally for a temperature and composition region of low-activity nuclear waste glasses containing over forty components, we have generated three linear models for viscosity as a function of temperature and composition. By identifying twenty glass viscosity-influencing components, Model A quantifies the effects of even relatively minor components, such as Cl, Cr2O3, F, P2O5, SO3, SnO2, TiO2, or V2O5. Such effects are mostly reported in the literature only qualitatively. Model B achieves a similar prediction accuracy after setting aside volatile components (Cl, F), whose concentrations may vary during glass processing, and Cr2O3 because of its standard error of determined component coefficient. A parsimonious Model C reduces the number of viscosity-influencing components to a mere seven: Al2O3, B2O3, CaO, Li2O, Na2O, SiO2, and Others. In each model, the Others component summarizes the fractions of the remaining components. For all three models, the component coefficients are determined with a high confidence (low standard error) and a high coefficient of determination: 0.972 for Model A, 0.970 for Model B, and 0.949 for Model C.