Methods for estimation of covariance matrices and covariance components for the Hanford Waste Vitrification Plant Process

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Description

The high-level waste (HLW) vitrification plant at the Hanford Site was being designed to transuranic and high-level radioactive waste in borosilicate class. Each batch of plant feed material must meet certain requirements related to plant performance, and the resulting class must meet requirements imposed by the Waste Acceptance Product Specifications. Properties of a process batch and the resultlng glass are largely determined by the composition of the feed material. Empirical models are being developed to estimate some property values from data on feed composition. Methods for checking and documenting compliance with feed and glass requirements must account for various types ... continued below

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80 p.

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Bryan, M. F.; Piepel, G. F. & Simpson, D. B. March 1996.

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  • Pacific Northwest Laboratory
    Publisher Info: Pacific Northwest Lab., Richland, WA (United States)
    Place of Publication: Richland, Washington

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Description

The high-level waste (HLW) vitrification plant at the Hanford Site was being designed to transuranic and high-level radioactive waste in borosilicate class. Each batch of plant feed material must meet certain requirements related to plant performance, and the resulting class must meet requirements imposed by the Waste Acceptance Product Specifications. Properties of a process batch and the resultlng glass are largely determined by the composition of the feed material. Empirical models are being developed to estimate some property values from data on feed composition. Methods for checking and documenting compliance with feed and glass requirements must account for various types of uncertainties. This document focuses on the estimation. manipulation, and consequences of composition uncertainty, i.e., the uncertainty inherent in estimates of feed or glass composition. Three components of composition uncertainty will play a role in estimating and checking feed and glass properties: batch-to-batch variability, within-batch uncertainty, and analytical uncertainty. In this document, composition uncertainty and its components are treated in terms of variances and variance components or univariate situations, covariance matrices and covariance components for multivariate situations. The importance of variance and covariance components stems from their crucial role in properly estimating uncertainty In values calculated from a set of observations on a process batch. Two general types of methods for estimating uncertainty are discussed: (1) methods based on data, and (2) methods based on knowledge, assumptions, and opinions about the vitrification process. Data-based methods for estimating variances and covariance matrices are well known. Several types of data-based methods exist for estimation of variance components; those based on the statistical method analysis of variance are discussed, as are the strengths and weaknesses of this approach.

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80 p.

Notes

OSTI as DE96008239

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  • Other Information: PBD: Mar 1996

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  • Other: DE96008239
  • Report No.: PNNL--11000
  • Report No.: PHTD--C93-05-01P
  • Grant Number: AC06-76RL01830
  • DOI: 10.2172/215713 | External Link
  • Office of Scientific & Technical Information Report Number: 215713
  • Archival Resource Key: ark:/67531/metadc666027

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  • March 1996

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  • June 29, 2015, 9:42 p.m.

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  • April 7, 2016, 6:22 p.m.

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Bryan, M. F.; Piepel, G. F. & Simpson, D. B. Methods for estimation of covariance matrices and covariance components for the Hanford Waste Vitrification Plant Process, report, March 1996; Richland, Washington. (digital.library.unt.edu/ark:/67531/metadc666027/: accessed November 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.