Total Measurement Uncertainty for the Plutonium Finishing Plant (PFP) Segmented Gamma Scan Assay System
This report presents the results of an evaluation of the Total Measurement Uncertainty (TMU) for the Canberra manufactured Segmented Gamma Scanner Assay System (SGSAS) as employed at the Hanford Plutonium Finishing Plant (PFP). In this document, TMU embodies the combined uncertainties due to all of the individual random and systematic sources of measurement uncertainty. It includes uncertainties arising from corrections and factors applied to the analysis of transuranic waste to compensate for inhomogeneities and interferences from the waste matrix and radioactive components. These include uncertainty components for any assumptions contained in the calibration of the system or computation of the data. Uncertainties are propagated at 1 sigma. The final total measurement uncertainty value is reported at the 95% confidence level. The SGSAS is a gamma assay system that is used to assay plutonium and uranium waste. The SGSAS system can be used in a stand-alone mode to perform the NDA characterization of a container, particularly for low to medium density (0-2.5 g/cc) container matrices. The SGSAS system provides a full gamma characterization of the container content. This document is an edited version of the Rocky Flats TMU Report for the Can Scan Segment Gamma Scanners, which are in use for the plutonium residues projects at the Rocky Flats plant. The can scan segmented gamma scanners at Rocky Flats are the same design as the PFP SGSAS system and use the same software (with the exception of the plutonium isotopics software). Therefore, all performance characteristics are expected to be similar. Modifications in this document reflect minor differences in the system configuration, container packaging, calibration technique, etc. These results are supported by the Quality Assurance Objective (QAO) counts, safeguards test data, calibration data, etc. for the PFP SGSAS system. Other parts of the TMU analysis utilize various modeling techniques such as Monte Carlo N-Particle (MCNP) and In Situ Object Counting Software (ISOCS).
- Research Organization:
- Fluor Hanford, Richland, WA (United States)
- Sponsoring Organization:
- USDOE Office of Environmental Management (EM) (US)
- DOE Contract Number:
- AC06-96RL13200
- OSTI ID:
- 807148
- Report Number(s):
- HNF-6944, Rev.2; ECN-666982; TRN: US200305%%216
- Resource Relation:
- Other Information: PBD: 6 Jun 2001
- Country of Publication:
- United States
- Language:
- English
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