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Introducing Robust Statistics in the Uncertainty Quantification of Nuclear Safeguards Measurements

Andrea Cerasa¹

¹European Commission, Joint Research Centre, Via E. Fermi 2479, 21027 Ispra, VA, Italy.

Entropy (Basel, Switzerland)

|August 26, 2022

Summary

Robust statistical methods enhance nuclear safeguards by improving uncertainty quantification. These methods limit bias in measurement data, ensuring more reliable outcomes for safeguarding nuclear materials.

Area of Science:

Nuclear safeguards
Statistical analysis
Measurement science

Background:

Nuclear safeguards involve verifying operator declarations against inspector measurements.
Deviations in data can arise from measurement system issues or intentional data falsification.
Unreliable statistical outcomes result from unaddressed data deviations.

Purpose of the Study:

To investigate the benefits of robust procedures in nuclear safeguards.
To introduce a robust estimator for measurement error model uncertainty components.
To demonstrate the capacity of robust procedures to improve statistical outcomes.

Main Methods:

Introduction of a robust estimator for uncertainty components.
Analysis of simulated and empirical data.
Application of robust statistical procedures.

Main Results:

Robust procedures effectively limit bias in nuclear safeguards data.
Simulated and empirical analyses confirm the efficacy of robust methods.
Improved statistical outcomes were observed using robust estimators.

Conclusions:

Robust procedures offer significant advantages for nuclear safeguards.
The developed robust estimator enhances uncertainty quantification for error variance.
Implementing robust methods is a key advancement in reliable nuclear safeguards.

Keywords:

ANOVA Q-estimator nuclear safeguards one-way random effect model robust statistics

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