Abstract

ABSTRACT The activation energy of glass melt viscosity, η, is nearly constant at temperatures at which η < 100 Pa s. Provided that the preexponential factor is a composition-independent constant, only the activation energy is a function of composition, and viscosity–composition relationships of utmost simplicity can be formulated to provide a welcome advantage in computational fluid dynamics modeling of glass melting furnaces processing multicomponent glasses. Using a dataset with over 3000 viscosity values acquired experimentally for a temperature and composition region of low-activity nuclear waste glasses, we have generated three linear models for viscosity as a function of temperature and composition. Model A quantifies the effects of 20 viscosity-influencing components. Model B achieves a similar prediction accuracy after setting aside volatile components, whose concentrations may vary during glass processing. 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.

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