Predicting primary crystalline phase and liquidus temperature above or below 1050{degrees}C as functions of glass composition

This report presents the results of applying statistical empirical modeling techniques to primary crystalline phase at the liquidus temperature (T{sub L}) and (ii) whether liquidus temperature is above or below 1050{degree}C (1OO{degree}C below a melting temperature of 1150{degree}C). Data used in modeling primary crystalline phase and liquidus temperate are from the Composition Variability Study (CVS) of Hanford waste glass compositions and properties. The majority of the 123 CVS glasses are categorized into one of 13 primary crystalline phases (at the liquidus temperature). They are also classified as to having T{sub L} Above or Below 1050{degree}C. Two common statistical methods used to model such categorical data are the multinomial logit and classification tree models. The classification tree models provided an overall better modeling approach than did the multinomial logit models. The performance of models in this report should be compared to the performance of the revised ``Development of Models and Software for Liquidus Temperature of Glasses of HWVP Products`` models from Ecole Polytechnique. If the Ecole Polytechnique models perform better than the models discussed in this report, no additional effort on these models would be needed. However, if the converse is true, it may be worthwhile to invest additional effort on statistical empirical modeling methods