JCGM 101-compliant uncertainty evaluation using virtual experiments

TL;DR

This paper extends Monte Carlo methods for uncertainty evaluation using virtual experiments to non-linear models, providing a practical reference approach aligned with JCGM 101 guidelines.

Contribution

It introduces a generalized Monte Carlo approach for uncertainty evaluation with virtual experiments in non-linear measurement models, filling a gap in current guidelines.

Findings

Method works for non-linear models

Numerical examples confirm theoretical results

Provides a practical reference for uncertainty evaluation

Abstract

Virtual experiments (VEs), a modern tool in metrology, can be used to help perform an uncertainty evaluation for the measurand. Current guidelines in metrology do not cover the many possibilities to incorporate VEs into an uncertainty evaluation, and it is often difficult to assess if the intended use of a VE complies with said guidelines. In recent work, it was shown that a VE can be used in conjunction with real measurement data and a Monte Carlo procedure to produce equal results to a supplement of the Guide to the Expression of Uncertainty in Measurement. However, this was shown only for linear measurement models. In this work, we extend this Monte Carlo approach to a common class of non-linear measurement models and more complex VEs, providing a reference approach for suitable uncertainty evaluations involving VEs. Numerical examples are given to show that the theoretical derivations hold in a practical scenario.