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TWRS privatization support project waste characterization database development
Publication year - 1995
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/212459
Subject(s) - characterization (materials science) , database , sample (material) , computer science , waste management , environmental science , data science , engineering , chemistry , materials science , nanotechnology , chromatography
Pacific Northwest National Laboratory requested support from ICF Kaiser Hanford Company in assembling radionuclide and chemical analyte sample data and inventory estimates for fourteen Hanford underground storage tanks: 241-AN-102, -104, -105, -106, and -107, 241-AP-102, -104, and -105, 241-AW-101, -103, and -105, 241 AZ-101 and -102; and 241-C-109. Sample data were assembled for sixteen radionuclides and thirty-five chemical analytes. The characterization data were provided to Pacific Northwest National Laboratory in support of the Tank Waste Remediation Services Privatization Support Project. The purpose of this report is to present the results and document the methodology used in preparing the waste characterization information data set to support the Tank Waste Remediation Services Privatization Support Project. This report describes the methodology used in assembling the waste characterization information and how that information was validated by a panel of independent technical reviewers. Also, contained in this report are the various data sets created: the master data set, a subset, and an unreviewed data set. The master data set contains waste composition information for Tanks 241-AN-102 and -107, 241-AP-102 and -105, 241-AW-101; and 241-AZ-101 and -102. The subset contains only the validated analytical sample data from the master data set. The unreviewed data set contains all collected but unreviewed sample data for Tanks 241-AN-104, -105, and -106; 241-AP-104; 241-AW-103 and-105; and 241-C-109. The methodology used to review the waste characterization information was found to be an accurate, useful way to separate the invalid or questionable data from the more reliable data. In the future, this methodology should be considered when validating waste characterization information

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