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BS ISO 11929-4:2020

Superseded

Superseded

A superseded Standard is one, which is fully replaced by another Standard, which is a new edition of the same Standard.

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Determination of the characteristic limits (decision threshold, detection limit and limits of the coverage interval) for measurements of ionizing radiation. Fundamentals and application Part 4: Guidelines to applications

Available format(s)

Hardcopy , PDF

Superseded date

09-08-2022

Language(s)

English

Published date

17-09-2020

€366.94
Excluding VAT

Committee
NCE/2
DocumentType
Standard
Pages
110
PublisherName
British Standards Institution
Status
Superseded
SupersededBy
Supersedes

This document specifies a procedure, in the field of ionizing radiation metrology, for the calculation of the “decision threshold”, the “detection limit” and the “limits of the coverage interval” for a non‑negative ionizing radiation measurand when counting measurements with preselection of time or counts are carried out. The measurand results from a gross count rate and a background count rate as well as from further quantities on the basis of a model of the evaluation. In particular, the measurand can be the net count rate as the difference of the gross count rate and the background count rate, or the net activity of a sample. It can also be influenced by calibration of the measuring system, by sample treatment and by other factors. ISO11929 has been divided into four parts covering elementary applications inISO11929‑1, advanced applications on the basis of the ISO/IECGuide98‑3:2008/Suppl.1 in ISO11929‑2, applications to unfolding methods in ISO11929‑3, and guidance to the application in ISO11929‑4. ISO11929‑1 covers basic applications of counting measurements frequently used in the field of ionizing radiation metrology. It is restricted to applications for which the uncertainties can be evaluated on the basis of the ISO/IECGuide98‑3 (JCGM2008). In ISO11929‑1:2019, Annex A the special case of repeated counting measurements with random influences and in ISO11929‑1:2019, AnnexB, measurements with linear analogous ratemeters are covered. ISO11929‑2 extends ISO11929‑1 to the evaluation of measurement uncertainties according to the ISO/IECGuide98‑3:2008/Suppl.1.ISO11929‑2 also presents some explanatory notes regarding general aspects of counting measurements and Bayesian statistics in measurements. ISO11929‑3 deals with the evaluation of measurements using unfolding methods and counting spectrometric multi-channel measurements if evaluated by unfolding methods, in particular, alpha- and gamma-spectrometric measurements. Further, it provides some advice how to deal with correlations and covariances. ISO11929‑4 gives guidance to the application of ISO11929(allparts), summarizing shortly the general procedure and then presenting a wide range of numerical examples. The examples cover elementary applications according to ISO11929‑1 and ISO11929‑2. The ISO11929(allparts) also applies analogously to other measurements of any kind if a similar model of the evaluation is involved. Further practical examples can be found in other International Standards, for example, see References[1 to 20]. NOTE A code system, named UncertRadio, is available allowing for calculations according to ISO11929‑1 to ISO11929‑3. UncertRadio[40][41] which can be downloaded for free from https://www.thuenen.de/en/fi/fields-of-activity/marine-environment/coordination-centre-of-radioactivity/uncertradio/. The download contains a setup installation file that copies all files and folders into a folder specified by the user. After installation one has to add information to the PATH of Windows as indicated by a pop‑up window during installation. English language can be chosen and extensive “help” information is available. Another tool is the package ‘metRology’[44] which is available for programming in R. It contains the two R functions ‘uncert’ and ‘uncertMC’ which perform the GUM-conform uncertainty propagation, either analytically or by the Monte Carlo method, respectively. Covariances/correlations of input quantities are included. Applying these two functions within iterations for decision threshold and the detection limit calculations simplifies the programming effort significantly. It is also possible to implement this document in a spreadsheet containing a Monte Carlo add-in or into other commercial mathematics software.

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