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The guide aims to outline uncertainty evaluation methods when using real measurements in conjunction with virtual experiments.

May 6, 2026Open Access

Good practice guide on uncertainty evaluation for virtual experiments in conjunction with real measurements

Key Points

The guide aims to outline uncertainty evaluation methods when using real measurements in conjunction with virtual experiments.
Describes uncertainty evaluation methods, including GUM approaches and Monte Carlo sampling.
Assesses limitations and properties of the evaluated methods.
Applies methods to three real measurement use cases.
Identifies effective uncertainty evaluation methods for virtual experiments and real measurements.
Provides insights into the application of digital twins in measuring uncertainty.

Abstract

This good practice guide (GPG) was written as part of the European Partnership on Metrology (EPM) project “Trustworthy virtual experiments and digital twins” (22DIT01 ViDiT), which has received funding from the European Partnership on Metrology, co-financed from the European Union’s Horizon Europe Research and Innovation Programme and by the Participating States. The aim of this GPG is to describe how to carry out uncertainty evaluation when there are real measurements available in conjunction with a virtual experiment, which models the measurement in a virtual environment. Several methods for uncertainty evaluation are presented and assessed in terms of their properties and limitations. These methods include approaches as documented in the GUM and its supplements, as well as alternative Monte Carlo sampling approaches and methods involving Bayesian inference. These methods will be applied and discussed in terms of three real measurement use cases.

Good practice guide on uncertainty evaluation for virtual experiments in conjunction with real measurements

Key Points

Abstract

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