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

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

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, Christian Rothleitner, and Daniel Heißelmann

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.