Structure of digital metrological twins  as software for uncertainty estimation

Poroskun, Ivan; Rothleitner, Christian; Heißelmann, Daniel

doi:https://doi.org/10.5194/jsss-11-75-2022

Articles | Volume 11, issue 1

J. Sens. Sens. Syst., 11, 75–82, 2022

https://doi.org/10.5194/jsss-11-75-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: Sensors and Measurement Science International SMSI 2021

J. Sens. Sens. Syst., 11, 75–82, 2022

https://doi.org/10.5194/jsss-11-75-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 11, issue 1

Regular research article 09 Mar 2022

Regular research article | 09 Mar 2022

Structure of digital metrological twins as software for uncertainty estimation

Ivan Poroskun et al.

Model code and software

Eigen v3 G. Guennebaud, B. Jacob, et al. https://eigen.tuxfamily.org

random, commit 639db9b I. Polishchuk https://github.com/effolkronium/random

Short summary

The paper proposes a structure for the creation of new simulation software for uncertainty estimation. The structure was derived from the well-established VCMM. To make it easy to apply the software structure to specific projects, a supporting software library (written in C++) was created. The library provides all the components necessary to create software for uncertainty estimation. The software structure and library proposed can be used in different domains of metrology.