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Title: KEY ELEMENTS OF CHARACTERIZING SAVANNAH RIVER SITE HIGH LEVEL WASTE SLUDGE INSOLUBLES THROUGH SAMPLING AND ANALYSIS

Abstract

Characterization of HLW is a prerequisite for effective planning of HLW disposition and site closure performance assessment activities. Adequate characterization typically requires application of a combination of data sources, including process knowledge, theoretical relationships, and real-waste analytical data. Consistently obtaining high quality real-waste analytical data is a challenge, particularly for HLW sludge insolubles, due to the inherent complexities associated with matrix heterogeneities, sampling access limitations, radiological constraints, analyte loss mechanisms, and analyte measurement interferences. Understanding how each of these complexities affects the analytical results is the first step to developing a sampling and analysis program that provides characterization data that are both meaningful and adequate. A summary of the key elements impacting SRS HLW sludge analytical data uncertainties is presented in this paper, along with guidelines for managing each of the impacts. The particular elements addressed include: (a) sample representativeness; (b) solid/liquid phase quantification effectiveness; (c) solids dissolution effectiveness; (d) analyte cross contamination, loss, and tracking; (e) dilution requirements; (f) interference removal; (g) analyte measurement technique; and (h) analytical detection limit constraints. A primary goal of understanding these elements is to provide a basis for quantifying total propagated data uncertainty.

Authors:
;
Publication Date:
Research Org.:
SRS
Sponsoring Org.:
USDOE
OSTI Identifier:
908211
Report Number(s):
LWO-PIT-2007-00061
TRN: US0703626
DOE Contract Number:  
DE-AC09-96SR18500
Resource Type:
Conference
Resource Relation:
Conference: Materials Science and Technology 2007
Country of Publication:
United States
Language:
English
Subject:
12 MANAGEMENT OF RADIOACTIVE WASTES, AND NON-RADIOACTIVE WASTES FROM NUCLEAR FACILITIES; SAVANNAH RIVER PLANT; HIGH-LEVEL RADIOACTIVE WASTES; SAMPLING; CHEMICAL ANALYSIS; PLANNING; RADIOACTIVE WASTE DISPOSAL; SLUDGES; RECOMMENDATIONS

Citation Formats

Reboul, S, and Barbara Hamm, B. KEY ELEMENTS OF CHARACTERIZING SAVANNAH RIVER SITE HIGH LEVEL WASTE SLUDGE INSOLUBLES THROUGH SAMPLING AND ANALYSIS. United States: N. p., 2007. Web.
Reboul, S, & Barbara Hamm, B. KEY ELEMENTS OF CHARACTERIZING SAVANNAH RIVER SITE HIGH LEVEL WASTE SLUDGE INSOLUBLES THROUGH SAMPLING AND ANALYSIS. United States.
Reboul, S, and Barbara Hamm, B. Thu . "KEY ELEMENTS OF CHARACTERIZING SAVANNAH RIVER SITE HIGH LEVEL WASTE SLUDGE INSOLUBLES THROUGH SAMPLING AND ANALYSIS". United States. doi:. https://www.osti.gov/servlets/purl/908211.
@article{osti_908211,
title = {KEY ELEMENTS OF CHARACTERIZING SAVANNAH RIVER SITE HIGH LEVEL WASTE SLUDGE INSOLUBLES THROUGH SAMPLING AND ANALYSIS},
author = {Reboul, S and Barbara Hamm, B},
abstractNote = {Characterization of HLW is a prerequisite for effective planning of HLW disposition and site closure performance assessment activities. Adequate characterization typically requires application of a combination of data sources, including process knowledge, theoretical relationships, and real-waste analytical data. Consistently obtaining high quality real-waste analytical data is a challenge, particularly for HLW sludge insolubles, due to the inherent complexities associated with matrix heterogeneities, sampling access limitations, radiological constraints, analyte loss mechanisms, and analyte measurement interferences. Understanding how each of these complexities affects the analytical results is the first step to developing a sampling and analysis program that provides characterization data that are both meaningful and adequate. A summary of the key elements impacting SRS HLW sludge analytical data uncertainties is presented in this paper, along with guidelines for managing each of the impacts. The particular elements addressed include: (a) sample representativeness; (b) solid/liquid phase quantification effectiveness; (c) solids dissolution effectiveness; (d) analyte cross contamination, loss, and tracking; (e) dilution requirements; (f) interference removal; (g) analyte measurement technique; and (h) analytical detection limit constraints. A primary goal of understanding these elements is to provide a basis for quantifying total propagated data uncertainty.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu May 24 00:00:00 EDT 2007},
month = {Thu May 24 00:00:00 EDT 2007}
}

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