Scaling factors for CANDU reactor waste: how reliable are they?
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Frank R. Greening
Abstract
This paper presents the results of a study of the use of the scaling factor method for the determination of the activities of the difficult to measure radionuclides – H-3, C-14, Ni-63, Sr-90, Pu-239/240 and Pu-214 – observed in CANDU radioactive waste. Twenty-six smear samples collected in the vault of Bruce Unit 1 during its refurbishment in the period 2009 to 2012 are used as surrogates for radioactive waste packages generated by the operation, maintenance, refurbishment and decommissioning of a CANDU reactor. A detailed analysis of the data presented in this paper shows that: (i) the activities of H-3 and C-14 cannot be reliably determined by the scaling factor method, and (ii) the activities of Ni-63, Sr-90, Pu-239/240 and Pu-214 estimated by the scaling factor method are typically in agreement with the measured activities to within only an order of magnitude of their true values. It is recommended that activities of CANDU rad-waste samples derived by the scaling factor method should be reported to only one significant figure to better reflect the limited precision and accuracy of this method.
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Research ethics: There are no ethical issues in my article.
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Author contributions: The author has accepted responsibility for the entire content of this manuscript and approved its submission.
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Competing interests: The author states there are no conflicts of interest.
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Research funding: None declared.
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Data availability: The raw data can be obtained on request from the corresponding author.
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Articles in the same Issue
- Frontmatter
- Evaluation of the optimum safety performance of the nuclear reactor compact grounding system under lightning strikes and ground fault
- An artificial neural network-based numerical estimation of the boiling pressure drop of different refrigerants flowing in smooth and micro-fin tubes
- Application of internal fire probabilistic risk assessment in design optimization for marine SMR
- Generic flame extension model development based on machine learning for NPPs fire hazard analysis (FHA)
- Comparison of thermal hydraulic performance between horizontal and vertical steam generators in nuclear power plants
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- A blockchain based scheme for distributed storage of nuclear power plant images
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