Selection of glasses in support of the Sludge Batch 9 variability study for coupled operation with the Salt Waste Processing Facility

Johnson, F. C.; Edwards, T. Bradley

doi:10.2172/1501825

Cited by 1 publication

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The initial focus of this work was to establish a method by which the densities of potential HLW glass compositions could be estimated 20‐24,50,51 . The estimation algorithm and parameterization presented here is also applicable to any facility producing glass and gives operators an a priori method for determining glass densities without the need for measurement.…”

Section: Resultsmentioning

confidence: 99%

Method for estimating the density of high‐level nuclear waste glass

Trivelpiece

Edwards

Johnson

et al. 2020

Int J of Appl Glass Sci

View full text Add to dashboard Cite

A database of over 1100 silicate glass compositions and densities was compiled and used to evaluate the efficacy of an algorithm for estimating the density of silicate glass compositions. We sought to develop a parsimonious algorithm based on the additivity of partial molar volumes of individual oxide components weighted by their mole fraction in a glass composition. Bound molar volumes were used for oxides in which the density of the oxide bound in a glass matrix was previously determined. The bound molar volumes were known for oxides covering 97.5 mole percent of the database compositional space. The measured glass densities were plotted against the estimated glass densities and a linear regression yielded an R2adj. = 0.95 and a slope and intercept of approximately one and zero, respectively. This regression suggests that glass densities estimated by the algorithm, within analysis uncertainty, are equal to the measured densities of the glasses. In addition to the development of the density estimation, we corroborated many of the referenced bound molar volume data used in the parameterization of the estimation algorithm via linear regression of the individual partial molar volumes vs the inverse measured densities (specific volumes) of the glasses in the database.

show abstract

Section: Resultsmentioning

confidence: 99%