Bayesian methods for the combination of core sampling data with historical models for tank characterization

A wide variety of information is available on the contents of the nuclear waste tanks at the Hanford site. This report describes an attempt to combine several sources of information using a Bayesian statistical approach. This methodology allows the combination of multiple disparate information sources. After each source of information is summarized in terms of a probability distribution function (pdf), Bayes` theorem is applied to combine them. This approach has been applied to characterizing tanks B-110, B-111, and B-201. These tanks were chosen for their simple waste matrices: B-110 and B-111 contain mostly 2C waste, and B-201 contains mostly 224 waste. Additionally,, the results of this analysis axe used to make predictions for tank T-111 (which contains both 2C and 224 waste). These predictions are compared to the estimates based on core samples from tank T-111